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Machine Learning (ML)
Deep Learning
Data ScienceResponsibilities
- Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
- Optimize and debug existing codes to make them scalable and improve performance
- Design, development, and delivery of tested code and machine learning models into production environments
- Work effectively in teams, managing and leading teams
- Provide effective, constructive feedback to the delivery leader
- Manage client expectations and work with an agile mindset with machine learning and AI technology
- Design and prototype data-driven solutions
Eligibility
- Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
- Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
- In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
- Expertise in writing scalable APIs for machine learning models
- Experience with maintaining code logs, task schedulers, and security
- Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
- Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch
Machine Learning (ML)Data ScienceRoles & Responsibilities:
-Adopt novel and breakthrough Deep Learning/Machine Learning technology to fully solve real world problems for different industries. -Develop prototypes of machine learning models based on existing research papers.
-Utilize published/existing models to meet business requirements. Tweak existing implementations to improve efficiencies and adapt for use-case variations.
-Optimize machine learning model training and inference time. -Work closely with development and QA teams in transitioning prototypes to commercial products
-Independently work end-to-end from data collection, preparation/annotation to validation of outcomes.
-Define and develop ML infrastructure to improve efficiency of ML development workflows.
Must Have:
- Experience in productizing and deployment of ML solutions.
- AI/ML expertise areas: Computer Vision with Deep Learning. Experience with object detection, classification, recognition; document layout and understanding tasks, OCR/ICR
. - Thorough understanding of full ML pipeline, starting from data collection to model building to inference.
- Experience with Python, OpenCV and at least a few framework/libraries (TensorFlow / Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)
- Years with relevant experience:
5+ -Experience or Knowledge in ML OPS.
Good to Have: NLP: Text classification, entity extraction, content summarization. AWS, Docker.
Machine Learning (ML)Data ScienceResponsibilities:
- Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
- Design and implement cloud solutions, build MLOps on the cloud (preferably AWS)
- Work with workflow orchestration tools like Kubeflow, Airflow, Argo, or similar tools
- Data science models testing, validation, and test automation.
- Communicate with a team of data scientists, data engineers, and architects, and document the processes.
Eligibility:
- Rich hands-on experience in writing object-oriented code using python
- Min 3 years of MLOps experience (Including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning, and Automated pipelines)
- Understanding of Data Structures, Data Systems, and software architecture
- Experience in using MLOps frameworks like Kubeflow, MLFlow, and Airflow Pipelines for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc. )
Data ScienceMachine Learning (ML)From building entire infrastructures or platforms to solving complex IT challenges, Cambridge Technology helps businesses accelerate their digital transformation and become AI-first businesses. With over 20 years of expertise as a technology services company, we enable our customers to stay ahead of the curve by helping them figure out the perfect approach, solutions, and ecosystem for their business. Our experts help customers leverage the right AI, big data, cloud solutions, and intelligent platforms that will help them become and stay relevant in a rapidly changing world.
No Of Positions: 1
Skills required:
- The ideal candidate will have a bachelor’s degree in data science, statistics, or a related discipline with 4-6 years of experience, or a master’s degree with 4-6 years of experience. A strong candidate will also possess many of the following characteristics:
- Strong problem-solving skills with an emphasis on achieving proof-of-concept
- Knowledge of statistical techniques and concepts (regression, statistical tests, etc.)
- Knowledge of machine learning and deep learning fundamentals
- Experience with Python implementations to build ML and deep learning algorithms (e.g., pandas, numpy, sci-kit-learn, Stats Models, Keras, PyTorch, etc.)
- Experience writing and debugging code in an IDE
- Experience using managed web services (e.g., AWS, GCP, etc.)
- Strong analytical and communication skills
- Curiosity, flexibility, creativity, and a strong tolerance for ambiguity
- Ability to learn new tools from documentation and internet resources.
Roles and responsibilities :
- You will work on a small, core team alongside other engineers and business leaders throughout Cambridge with the following responsibilities:
- Collaborate with client-facing teams to design and build operational AI solutions for client engagements.
- Identify relevant data sources for data wrangling and EDA
- Identify model architectures to use for client business needs.
- Build full-stack data science solutions up to MVP that can be deployed into existing client business processes or scaled up based on clear documentation.
- Present findings to teammates and key stakeholders in a clear and repeatable manner.
Experience :
2 - 14 Yrs
Data ScienceMachine Learning (ML)
PythonDeep LearningJOB TITLE - Product Development Engineer - Machine Learning
● Work Location: Hyderabad
● Full-time
Company Description
Phenom People is the leader in Talent Experience Marketing (TXM for short). We’re an early-stage startup on a mission to fundamentally transform how companies acquire talent. As a category creator, our goals are two-fold: to educate talent acquisition and HR leaders on the benefits of TXM and to help solve their recruiting pain points.
Job Responsibilities:
- Design and implement machine learning, information extraction, probabilistic matching algorithms and models
- Research and develop innovative, scalable and dynamic solutions to hard problems
- Work closely with Machine Learning Scientists (PhDs), ML engineers, data scientists and data engineers to address challenges head-on.
- Use the latest advances in NLP, data science and machine learning to enhance our products and create new experiences
- Scale machine learning algorithm that powers our platform to support our growing customer base and increasing data volume
- Be a valued contributor in shaping the future of our products and services
- You will be part of our Data Science & Algorithms team and collaborate with product management and other team members
- Be part of a fast pace, fun-focused, agile team
Job Requirement:
- 4+ years of industry experience
- Ph.D./MS/B.Tech in computer science, information systems, or similar technical field
- Strong mathematics, statistics, and data analytics
- Solid coding and engineering skills preferably in Machine Learning (not mandatory)
- Proficient in Java, Python, and Scala
- Industry experience building and productionizing end-to-end systems
- Knowledge of Information Extraction, NLP algorithms coupled with Deep Learning
- Experience with data processing and storage frameworks like Hadoop, Spark, Kafka etc.
Position Summary
We’re looking for a Machine Learning Engineer to join our team of Phenom. We are expecting the below points to full fill this role.
- Capable of building accurate machine learning models is the main goal of a machine learning engineer
- Linear Algebra, Applied Statistics and Probability
- Building Data Models
- Strong knowledge of NLP
- Good understanding of multithreaded and object-oriented software development
- Mathematics, Mathematics and Mathematics
- Collaborate with Data Engineers to prepare data models required for machine learning models
- Collaborate with other product team members to apply state-of-the-art Ai methods that include dialogue systems, natural language processing, information retrieval and recommendation systems
- Build large-scale software systems and numerical computation topics
- Use predictive analytics and data mining to solve complex problems and drive business decisions
- Should be able to design the accurate ML end-to-end architecture including the data flows, algorithm scalability, and applicability
- Tackle situations where problem is unknown and the Solution is unknown
- Solve analytical problems, and effectively communicate methodologies and results to the customers
- Adept at translating business needs into technical requirements and translating data into actionable insights
- Work closely with internal stakeholders such as business teams, product managers, engineering teams, and customer success teams.
Benefits
- Competitive salary for a startup
- Gain experience rapidly
- Work directly with the executive team
- Fast-paced work environment
About Phenom People
At PhenomPeople, we believe candidates (Job seekers) are consumers. That’s why we’re bringing e-commerce experience to the job search, with a view to convert candidates into applicants. The Intelligent Career Site™ platform delivers the most relevant and personalized job search yet, with a career site optimized for mobile and desktop interfaces designed to integrate with any ATS, tailored content selection like Glassdoor reviews, YouTube videos and LinkedIn connections based on candidate search habits and an integrated real-time recruiting analytics dashboard.
Use Company career sites to reach candidates and encourage them to convert. The Intelligent Career Site™ offers a single platform to serve candidates a modern e-commerce experience from anywhere on the globe and on any device.
We track every visitor that comes to the Company career site. Through fingerprinting technology, candidates are tracked from the first visit and served jobs and content based on their location, click-stream, behavior on site, browser and device to give each visitor the most relevant experience.
Like consumers, candidates research companies and read reviews before they apply for a job. Through our understanding of the candidate journey, we are able to personalize their experience and deliver relevant content from sources such as corporate career sites, Glassdoor, YouTube and LinkedIn.
We give you clear visibility into the Company's candidate pipeline. By tracking up to 450 data points, we build profiles for every career site visitor based on their site visit behavior, social footprint and any other relevant data available on the open web.
Gain a better understanding of Company’s recruiting spending and where candidates convert or drop off from Company’s career site. The real-time analytics dashboard offers companies actionable insights on optimizing source spending and the candidate experience.
Kindly explore about the company phenom (https://www.phenom.com/">https://www.phenom.com/)
Youtube - https://www.youtube.com/c/PhenomPeople">https://www.youtube.com/c/PhenomPeople
LinkedIn - https://www.linkedin.com/company/phenompeople/">https://www.linkedin.com/company/phenompeople/
https://www.phenom.com/">Phenom | Talent Experience Management
Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.
Roles & Responsibilities:
Work on implementation of real-time and batch data pipelines for disparate data sources.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
- Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
- Identify improvement areas in the current data system and implement optimizations.
- Work on specific areas of data governance including metadata management and data quality management.
- Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
- Develop Proof-of-Concepts to validate new technology solutions or advancements.
- Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
- Work on building intelligent systems using various AI/ML algorithms.
Desired Experience/Skill:
- Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
- Experience with private and public cloud architectures with pros/cons.
- Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
- Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
- Knowledge of Kafka, Redis is preferred
- Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
Data ScienceMachine Learning (ML)
Data AnalyticsDATA SCIENTIST-MACHINE LEARNING
GormalOne LLP. Mumbai IN
Job Description
GormalOne is a social impact Agri tech enterprise focused on farmer-centric projects. Our vision is to make farming highly profitable for the smallest farmer, thereby ensuring India's “Nutrition security”. Our mission is driven by the use of advanced technology. Our technology will be highly user-friendly, for the majority of farmers, who are digitally naive. We are looking for people, who are keen to use their skills to transform farmers' lives. You will join a highly energized and competent team that is working on advanced global technologies such as OCR, facial recognition, and AI-led disease prediction amongst others.
GormalOne is looking for a machine learning engineer to join. This collaborative yet dynamic, role is suited for candidates who enjoy the challenge of building, testing, and deploying end-to-end ML pipelines and incorporating ML Ops best practices across different technology stacks supporting a variety of use cases. We seek candidates who are curious not only about furthering their own knowledge of ML Ops best practices through hands-on experience but can simultaneously help uplift the knowledge of their colleagues.
Location: Bangalore
Roles & Responsibilities
- Individual contributor
- Developing and maintaining an end-to-end data science project
- Deploying scalable applications on different platform
- Ability to analyze and enhance the efficiency of existing products
What are we looking for?
- 3 to 5 Years of experience as a Data Scientist
- Skilled in Data Analysis, EDA, Model Building, and Analysis.
- Basic coding skills in Python
- Decent knowledge of Statistics
- Creating pipelines for ETL and ML models.
- Experience in the operationalization of ML models
- Good exposure to Deep Learning, ANN, DNN, CNN, RNN, and LSTM.
- Hands-on experience in Keras, PyTorch or Tensorflow
Basic Qualifications
- Tech/BE in Computer Science or Information Technology
- Certification in AI, ML, or Data Science is preferred.
- Master/Ph.D. in a relevant field is preferred.
Preferred Requirements
- Exp in tools and packages like Tensorflow, MLFlow, Airflow
- Exp in object detection techniques like YOLO
- Exposure to cloud technologies
- Operationalization of ML models
- Good understanding and exposure to MLOps
Kindly note: Salary shall be commensurate with qualifications and experience
Data ScienceMachine Learning (ML)Location: Ahmedabad / Pune
Team: Technology
Company Profile
InFoCusp is a company working in the broad field of Computer Science, Software Engineering, and Artificial Intelligence (AI). It is headquartered in Ahmedabad, India, having a branch office in Pune.
We have worked on / are working on AI projects / algorithms-heavy projects with applications ranging in finance, healthcare, e-commerce, legal, HR/recruiting, pharmaceutical, leisure sports and computer gaming domains. All of this is based on the core concepts of data science,
computer vision, machine learning (with emphasis on deep learning), cloud computing, biomedical signal processing, text and natural language processing, distributed systems, embedded systems and the Internet of Things.
PRIMARY RESPONSIBILITIES:
● Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
● Architecting large scale data analytics/modeling systems.
● Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
● Analyzing data collected from various sources,
● Evaluate and validate the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
● Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
● Evaluating new machine learning methods and adapting them for our
purposes.
● Feature engineering to add new features that improve model
performance.
KNOWLEDGE AND SKILL REQUIREMENTS:
● Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing with at least 3 years of professional work experience working on real-world data.
● Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
● Knowledge of machine learning libraries Tensorflow, Jax, Keras, scikit-learn, pyTorch. Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, advanced probability concepts
● Ability to perform both independent and collaborative research.
● Excellent written and spoken communication skills.
● A proven ability to work in a cross-discipline environment in defined time frames. Knowledge and experience of deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.
● Knowledge of systems engineering is a big plus.
● Some experience in project management and mentoring is also a big plus.
EDUCATION:
- B.E.\B. Tech\B.S. candidates' entries with significant prior experience in the aforementioned fields will be considered.
- M.E.\M.S.\M. Tech\PhD preferably in fields related to Computer Science with experience in machine learning, image and signal processing, or statistics preferred.
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
Deep LearningPythonWho Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
Machine Learning (ML)Data ScienceDeep LearningWho Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
PythonMachine Learning (ML)Data ScienceDo you want to help build real technology for a meaningful purpose? Do you want to contribute to making the world more sustainable, advanced and accomplished extraordinary precision in Analytics?
What is your role?
As a Computer Vision & Machine Learning Engineer at Datasee.AI, you’ll be core to the development of our robotic harvesting system’s visual intelligence. You’ll bring deep computer vision, machine learning, and software expertise while also thriving in a fast-paced, flexible, and energized startup environment. As an early team member, you’ll directly build our success, growth, and culture. You’ll hold a significant role and are excited to grow your role as Datasee.AI grows.
What you’ll do
- You will be working with the core R&D team which drives the computer vision and image processing development.
- Build deep learning model for our data and object detection on large scale images.
- Design and implement real-time algorithms for object detection, classification, tracking, and segmentation
- Coordinate and communicate within computer vision, software, and hardware teams to design and execute commercial engineering solutions.
- Automate the workflow process between the fast-paced data delivery systems.
What we are looking for
- 1 to 3+ years of professional experience in computer vision and machine learning.
- Extensive use of Python
- Experience in python libraries such as OpenCV, Tensorflow and Numpy
- Familiarity with a deep learning library such as Keras and PyTorch
- Worked on different CNN architectures such as FCN, R-CNN, Fast R-CNN and YOLO
- Experienced in hyperparameter tuning, data augmentation, data wrangling, model optimization and model deployment
- B.E./M.E/M.Sc. Computer Science/Engineering or relevant degree
- Dockerization, AWS modules and Production level modelling
- Basic knowledge of the Fundamentals of GIS would be added advantage
Prefered Requirements
- Experience with Qt, Desktop application development, Desktop Automation
- Knowledge on Satellite image processing, Geo-Information System, GDAL, Qgis and ArcGIS
About Datasee.AI:
Datasee>AI, Inc. is an AI driven Image Analytics company offering Asset Management solutions for industries in the sectors of Renewable Energy, Infrastructure, Utilities & Agriculture. With core expertise in Image processing, Computer Vision & Machine Learning, Takvaviya’s solution provides value across the enterprise for all the stakeholders through a data driven approach.
With Sales & Operations based out of US, Europe & India, Datasee.AI is a team of 32 people located across different geographies and with varied domain expertise and interests.
A focused and happy bunch of people who take tasks head-on and build scalable platforms and products.
Machine Learning (ML)Deep LearningIntroduction
http://www.synapsica.com/">Synapsica is a https://yourstory.com/2021/06/funding-alert-synapsica-healthcare-ivycap-ventures-endiya-partners/">series-A funded HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don't have to rely on cryptic 2 liners given to them as a diagnosis.
Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting. We are backed by IvyCap, Endia Partners, YCombinator and other investors from India, US, and Japan. We are proud to have GE and The Spinal Kinetics as our partners. Here’s a small sample of what we’re building: https://www.youtube.com/watch?v=FR6a94Tqqls">https://www.youtube.com/watch?v=FR6a94Tqqls
Your Roles and Responsibilities
Synapsica is looking for a Principal AI Researcher to lead and drive AI based research and development efforts. Ideal candidate should have extensive experience in Computer Vision and AI Research, either through studies or industrial R&D projects and should be excited to work on advanced exploratory research and development projects in computer vision and machine learning to create the next generation of advanced radiology solutions.
The role involves computer vision tasks including development customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc.), and traditional Image Processing (OpenCV, etc.). The role is research-focused and would involve going through and implementing existing research papers, deep dive of problem analysis, frequent review of results, generating new ideas, building new models from scratch, publishing papers, automating and optimizing key processes. The role will span from real-world data handling to the most advanced methods such as transfer learning, generative models, reinforcement learning, etc., with a focus on understanding quickly and experimenting even faster. Suitable candidate will collaborate closely both with the medical research team, software developers and AI research scientists. The candidate must be creative, ask questions, and be comfortable challenging the status quo. The position is based in our Bangalore office.
Primary Responsibilities
- Interface between product managers and engineers to design, build, and deliver AI models and capabilities for our spine products.
- Formulate and design AI capabilities of our stack with special focus on computer vision.
- Strategize end-to-end model training flow including data annotation, model experiments, model optimizations, model deployment and relevant automations
- Lead teams, engineers, and scientists to envision and build new research capabilities and ensure delivery of our product roadmap.
- Organize regular reviews and discussions.
- Keep the team up-to-date with latest industrial and research updates.
- Publish research and clinical validation papers
Requirements
- 6+ years of relevant experience in solving complex real-world problems at scale using computer vision-based deep learning.
- Prior experience in leading and managing a team.
- Strong problem-solving ability
- Prior experience with Python, cuDNN, Tensorflow, PyTorch, Keras, Caffe (or similar Deep Learning frameworks).
- Extensive understanding of computer vision/image processing applications like object classification, segmentation, object detection etc
- Ability to write custom Convolutional Neural Network Architecture in Pytorch (or similar)
- Background in publishing research papers and/or patents
- Computer Vision and AI Research background in medical domain will be a plus
- Experience of GPU/DSP/other Multi-core architecture programming
- Effective communication with other project members and project stakeholders
- Detail-oriented, eager to learn, acquire new skills
- Prior Project Management and Team Leadership experience
- Ability to plan work and meet the deadline
Data ScienceMachine Learning (ML)Sizzle is an exciting new startup that’s changing the world of gaming. At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar engineer that is well versed with AI and audio technologies around audio detection, speech-to-text, interpretation, and sentiment analysis.
You will be responsible for:
Developing audio algorithms to detect key moments within popular online games, such as:
Streamer speaking, shouting, etc.
Gunfire, explosions, and other in-game audio events
Speech-to-text and sentiment analysis of the streamer’s narration
Leveraging baseline technologies such as TensorFlow and others -- and building models on top of them
Building neural network architectures for audio analysis as it pertains to popular games
Specifying exact requirements for training data sets, and working with analysts to create the data sets
Training final models, including techniques such as transfer learning, data augmentation, etc. to optimize models for use in a production environment
Working with back-end engineers to get all of the detection algorithms into production, to automate the highlight creation
You should have the following qualities:
Solid understanding of AI frameworks and algorithms, especially pertaining to audio analysis, speech-to-text, sentiment analysis, and natural language processing
Experience using Python, TensorFlow and other AI tools
Demonstrated understanding of various algorithms for audio analysis, such as CNNs, LSTM for natural language processing, and others
Nice to have: some familiarity with AI-based audio analysis including sentiment analysis
Familiarity with AWS environments
Excited about working in a fast-changing startup environment
Willingness to learn rapidly on the job, try different things, and deliver results
Ideally a gamer or someone interested in watching gaming content online
Skills:
Machine Learning, Audio Analysis, Sentiment Analysis, Speech-To-Text, Natural Language Processing, Neural Networks, TensorFlow, OpenCV, AWS, Python
Work Experience: 2 years to 10 years
About Sizzle
Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Presently, there are over 700 million fans around the world that watch gaming videos on Twitch and YouTube. Sizzle is creating a new highlights experience for these fans, so they can catch up on their favorite streamers and esports leagues. Sizzle is available at http://www.sizzle.gg">www.sizzle.gg.
Data SciencePythonDevelop state of the art algorithms in the fields of Computer Vision, Machine Learning and Deep Learning.
Provide software specifications and production code on time to meet project milestones Qualifications
BE or Master with 3+ years of experience
Must have Prior knowledge and experience in Image processing and Video processing • Should have knowledge of object detection and recognition
Must have experience in feature extraction, segmentation and classification of the image
Face detection, alignment, recognition, tracking & attribute recognition
Excellent Understanding and project/job experience in Machine learning, particularly in areas of Deep Learning – CNN, RNN, TENSORFLOW, KERAS etc.
Real world expertise in deep learning- applied to Computer Vision problems • Strong foundation in Mathematics
Strong development skills in Python
Must have worked upon Vision and deep learning libraries and frameworks such as Opencv, Tensorflow, Pytorch, keras
Quick learner of new technologies
Ability to work independently as well as part of a team
Knowledge of working closely with Version Control(GIT)
Machine Learning (ML)PythonAdvanced degree in computer science, math, statistics or a related discipline ( Must have master degree )
Extensive data modeling and data architecture skills
Programming experience in Python, R
Background in machine learning frameworks such as TensorFlow or Keras
Knowledge of Hadoop or another distributed computing systems
Experience working in an Agile environment
Advanced math skills (Linear algebra
Discrete math
Differential equations (ODEs and numerical)
Theory of statistics 1
Numerical analysis 1 (numerical linear algebra) and 2 (quadrature)
Abstract algebra
Number theory
Real analysis
Complex analysis
Intermediate analysis (point set topology)) ( important )
Strong written and verbal communications
Hands on experience on NLP and NLG
Experience in advanced statistical techniques and concepts. ( GLM/regression, Random forest, boosting, trees, text mining ) and experience with application.
Machine Learning (ML)Deep LearningJob Description :
Sr. Machine Learning Engineer will support our various business vertical teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Accountabilities :
- Collaborate with product management and engineering departments to understand company needs and devise possible solutions
- Keep up-to-date with latest technology trends
- Communicate results and ideas to key decision makers
- Implement new statistical or other mathematical methodologies as needed for specific models or analysis
- Optimize joint development efforts through appropriate database use and project design
Skills & Requirements :
Technical Skills :
- Demonstrated skill in the use of one or more analytic software tools or languages (e.g., R, Python, Pyomo, Julia/Jump, Matlab, SAS,SQL)
- Demonstrated skill at data cleansing, data quality assessment, and using analytics for data assessment
- End-to-end system design: data analysis, feature engineering, technique selection & implementation, debugging, and maintenance in production.
- Profound understanding of skills like outlier handling, data imputation, bias, variance, cross validation etc.
- Demonstrated skill in modeling techniques, including but not limited to Predictive modeling, Supervised learning, Unsupervised learning, Machine Learning, Statistical Modeling, Natural language processing, Recommendation engines,
- Demonstrated skill in analytic prototyping, analytic scaling, and solutions integration
- Developing hypotheses and set up your own problem frameworks to test for the best solutions
- Knowledge of data visualization tools - ggplot, Dash, d3.js and Matplottlib (or any other data visualization like Tableau, Qlikview)
- Generating insights for a business context
Desirable :
- Experience with cloud technologies for building, deploying and delivering data science applications is desired (preferably in Microsoft Azure)
- Experience in Tensorflow, Keras, Theano, Text Mining is desirable but not mandatory
- Experience to work in Agile and DevOps processes.
Core Skills :
- Bachelor or master degree in information technology, computer science, business administration or a related discipline.
- Certified in Agile Product Owner / SCRUM master and/or other Agile techniques
Leadership Skills :
- Strong stakeholder management and influencing skills. Able to articulate a vision and build support for that vision in the wider team and organization.
- Ability to self-start and direct efforts based on high-level business objectives
- Strong collaboration and leadership skills with the ability to coach and develop teams to meet new challenges.
- Strong interpersonal, communication, facilitation and presentation skills.
- Work through complex interfaces across organizational and geographic boundaries
- Excellent analytical, planning and problem solving skills
Job Experience Requirements :
- Utilize an advanced knowledge level of the Data Science Toolbox to participate in the entire Data Science Project Life cycle and execute end-to-end Data Science project
- Work end-to-end on Data Science developments contributing to all aspects of the project life cycle
- Keep customers as focus of analysis insight and recommendation.
- Help define business objectives/customer needs by capturing the right requirements from the right customers.
- Can take defined problems and identify resolution paths and opportunities to solve them; which you validate by defining hypotheses and driving experiments
- Can identify unstructured problems and articulate opportunities to form new analytics project ideas
- Use and understand the key performance indicators (KPIs) and diagnostics to measure performance against business goals
- Compile integrate and analyze data from multiple sources to identify trends expose new opportunities and answer ongoing business questions
- Execute hypothesis-driven analysis to address business questions issues and opportunities
- Build validate and manage advanced models (e.g. explanatory predictive) using statistical and/or other analytical methods
- Are familiar working within Agile Project Management methodologies / structures
- Analyze results using statistical methods and work with senior team members to make recommendations to improve customer experience and business results
- Have the ability to conceptualize formulate prototype and implement algorithms to capture customer behavior and solve business problems
- Analyze results using statistical methods to make recommendations to improve customer experience and business results
Hammoq Inc is a rapidly growing startup in the reselling sector. Our app provides product listings, cross-platform data analytics, and Cross-platform delisting as our core services.
Launched Web app in 2020 and iOS app at the start of 2021, we are continuing our exponential growth, and we were hoping you could play a core role in our mission.
Hammoq is looking for a Senior ML/Machine Vision Architect / Researcher, an expert in Deep Learning, to join our passionate developers' team to create our unique SaaS web app.
The ideal candidate will be responsible for developing new Machine Learning / Machine vision models according to the business needs.
*What you'll do
- You’ll lead the ML R&D process at Hammoq.
- You will build ML architectures to optimise the process.
- You'll collaborate with our hardworking, nimble, and supportive team through daily standups, company presentations, product demos, slack discussions
- You'll work on solving machine vision / Machine Learning problems and implementations.
- You'll use ML libraries of IOS and Android to build and run models on the mobile devices
Skills and expertise that will help you succeed
- Must have experience working with OpenCV, TensorFlow, and Keras environment
- Must have the ability to develop your own models.
- Working experience of training and deploying computer vision models
- Experience in Computer Vision and Machine Learning (including Deep Learning) algorithms.
- Experience in image analytics - including feature extraction, object detection, classification, and tracking
- Experience in image manipulation
- PhD in Computer Vision , Machine Learning, Machine Vision or any related field is a must.
- Strong programming skills in Python, including NumPy, Scikit Learn, Pandas, and Matplotlib
- Self-governing analytical problem-solving skills for efficient and uninterrupted development of solutions
- Strong communications skills for an adequate description of technical concepts to others
Nice to have
- Experience in building APIs implementing ML models
- Knowledge or basic understanding of any Cloud ML technologies or Cloud ML service providers.
- Experience in the e-commerce industry
Machine Learning (ML)PythonResponsibilities
-
Create data funnels to feed into models via web, structured and unstructured data
-
Maintain coding standards using SDLC, Git, AWS deployments etc
-
Keep abreast of developments in the field
-
Deploy models in production and monitor them
-
Documentations of processes and logic
-
Take ownership of the solution from code to deployment and performance
Data ScienceDeep LearningMachine Learning (ML)● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypotheses through theoretical and empirical approaches.
● Productize has proven or working models into production-quality code.
● Collaborate with product management, marketing, and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with the latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision-makers.
● File patents for innovative solutions that add to the company's IP portfolio
Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/Ph.D. in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes ( only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Fluency in analytical tools such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis
● Strong communication and collaboration skills.
Data ScienceDeep LearningMachine Learning (ML)Responsibilities
-
Building out and manage a young data science vertical within the organization
-
Provide technical leadership in the areas of machine learning, analytics, and data sciences
-
Work with the team and create a roadmap to solve the company’s requirements by solving data-mining, analytics, and ML problems by Identifying business problems that could be solved using Data Science and scoping it out end to end.
-
Solve business problems by applying advanced Machine Learning algorithms and complex statistical models on large volumes of data.
-
Develop heuristics, algorithms, and models to deanonymize entities on public blockchains
-
Data Mining - Extend the organization’s proprietary dataset by introducing new data collection methods and by identifying new data sources.
-
Keep track of the latest trends in cryptocurrency usage on open-web and dark-web and develop counter-measures to defeat concealment techniques used by criminal actors.
-
Develop in-house algorithms to generate risk scores for blockchain transactions.
-
Work with data engineers to implement the results of your work.
-
Assemble large, complex data sets that meet functional / non-functional business requirements.
-
Build, scale and deploy holistic data science products after successful prototyping.
-
Clearly articulate and present recommendations to business partners, and influence future plans based on insights.
Preferred Experience
-
>8+ years of relevant experience as a Data Scientist or Analyst. A few years of work experience solving NLP problems or other ML problems is a plus
-
Must have previously managed a team of at least 5 data scientists or analysts or demonstrate that they have prior experience in scaling a data science function from the ground
-
Good understanding of python, bash scripting, and basic cloud platform skills (on GCP or AWS)
-
Excellent communication skills and analytical skills
What you’ll get
-
Work closely with the Founders in helping grow the organization to the next level alongside some of the best and brightest talents around you
-
An excellent culture, we encourage collaboration, growth, and learning amongst the team
-
Competitive salary and equity
-
An autonomous and flexible role where you will be trusted with key tasks.
-
An opportunity to have a real impact and be part of a company with purpose.
Deep Learning|
Sr AI Scientist, Bengaluru |
Job Description
Introduction
Synapsica is a growth stage HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective, while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don’t have to rely on cryptic 2 liners given to them as diagnosis. Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting. We are backed by YCombinator and other investors from India, US and Japan. We are proud to have GE, AIIMS, the Spinal Kinetics as our partners.
Your Roles and Responsibilities
The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc.) and traditional Image Processing (OpenCV etc.). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- 4+ years of relevant experience in solving complex real-world problems at scale via computer vision based deep learning.
- Strong problem-solving ability
- Prior experience with Python, cuDNN, Tensorflow, PyTorch, Keras, Caffe (or similar Deep Learning frameworks).
- Extensive understanding of computer vision/image processing applications like object classification, segmentation, object detection etc
- Ability to write custom Convolutional Neural Network Architecture in Pytorch (or similar)
- Experience of GPU/DSP/other Multi-core architecture programming
- Effective communication with other project members and project stakeholders
- Detail-oriented, eager to learn, acquire new skills
- Prior Project Management and Team Leadership experience
- Ability to plan work and meet deadlines
Data SciencePythonDeep LearningData ScienceMachine Learning (ML)Python- Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
- Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
- Own the end-end process, from recognizing the problem to implementing the solution.
- Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
- Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.
Skills and Qualification
- 12 to 15 yrs of experience.
- An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
- Experience with text mining, parsing, and classification using state-of-the-art techniques.
- Experience with information retrieval, Natural Language Processing, Natural Language
- Understanding and Neural Language Modeling.
- Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
- Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
- Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
- Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.
Deep LearningPythonMachine Learning (ML)WE ARE GRAPHENE
Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.
Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.
Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.
We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!
WHAT WILL THE ENGINEER-ML DO?
- Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
- Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
- Career Progression: Senior ML Engineer, ML Architect
YOU CAN EXPECT TO
- Work in a product-development team capable of independently authoring software products.
- Guide junior programmers, set up the architecture, and follow modular development approaches.
- Design and develop code which is well documented.
- Optimize of the application for maximum speed and scalability
- Adhere to the best Information security and Devops practices.
- Research and develop new approaches to problems.
- Design and implement schemas and databases with respect to the AI application
- Cross-pollinated with other teams.
HARD AND SOFT SKILLS
Must Have
- Problem-solving abilities
- Extremely strong programming background – data structures and algorithm
- Advanced Machine Learning: TensorFlow, Keras
- Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
- Experience with OOPs and design patterns
- Exposure to RDBMS/NoSQL
- Test Driven Development Methodology
Good to Have
- Working in cloud-native environments (preferably Azure)
- Microservices
- Enterprise Design Patterns
- Microservices Architecture
- Distributed Systems
Data Science
R ProgrammingPythonMachine Learning (ML)- 3+ years experience in practical implementation and deployment of ML based systems preferred.
- BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
- Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
- Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
- Experience in working on modeling graph structures related to spatiotemporal systems
- Programming skills in Python
- Experience in developing and deploying on cloud (AWS or Google or Azure)
- Good verbal and written communication skills
- Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow
Machine Learning (ML)Deep LearningAbout Turing:
Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.
We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:
- Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
- Executives from Google, Facebook, Square, Amazon, and Twitter
- Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
- Cyan Banister
- Founder of Upwork (Beerud Sheth)
We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month.
Some articles about Turing:
- https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
- https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
- https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
- https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.
Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.
About the role:
Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us.
We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc.
A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job.
You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words.
As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).
This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&;hl=en">Google Scholar profile.
Responsibilities:
- Enhance our existing machine learning systems using your core coding skills and ML knowledge.
- Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
- Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
- Design features and builds large scale recommendation systems to improve targeting and engagement.
- Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.
Minimum Requirements:
- BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
- Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
- Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
- 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
- Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
- Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
- Good understanding of mathematical foundations of machine learning algorithms.
- Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).
Other Nice-to-have Requirements:
- First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals.
- Strong performance in Kaggle competitions.
- 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
- Strong communication skills.
- Experienced in leading large-scale multi-engineering projects.
- Flexible, and a positive team player with outstanding interpersonal skills.
India's first Options Trading Analytics platform on mobile.
Location : Andheri East
Notice Period: Immediate-15 days
Responsibilities:
1. Study and transform data science prototypes.
2. Design NLP applications.
3. Select appropriate annotated datasets for Supervised Learning methods.
4. Find and implement the right algorithms and tools for NLP tasks.
5. Develop NLP systems according to requirements.
6. Train the developed model and run evaluation experiments.
7. Perform statistical analysis of results and refine models.
8. Extend ML libraries and frameworks to apply in NLP tasks.
9. Use effective text representations to transform natural language into useful features.
10. Develop APIs to deliver deciphered results, optimized for time and memory.
Requirements:
1. Proven experience as an NLP Engineer of at least one year.
2. Understanding of NLP techniques for text representation, semantic extraction techniques, data
structures and modeling.
3. Ability to effectively design software architecture.
4. Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment
analysis etc), statistics and classification algorithms.
5. Hands on Experience of Knowledge of Python of more than a year.
6. Ability to write robust and testable code.
7. Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
8. Strong communication skills.
9. An analytical mind with problem-solving abilities.
10. Bachelor Degree in Computer Science, Mathematics, Computational Linguistics.
Machine Learning (ML)Data ScienceDeep Learningalong with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying
differences in data distribution that could affect performance when deploying the model
in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production
Data ScienceDeep LearningPythonJob Description
We are looking for a data scientist that will help us to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
Skills and Qualifications
- Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
- Experience with Deep Learning preferred.
- Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Great communication skills
- Proficiency in using query languages such as SQL, Hive, Pig
- Good applied statistics skills, such as statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality
PythonMachine Learning (ML)Deep Learning2. Should understand the importance and know-how of taking the machine-learning-based solution to the consumer.
3. Hands-on experience with statistical, machine-learning tools and techniques
4. Good exposure to Deep learning libraries like Tensorflow, PyTorch.
5. Experience in implementing Deep Learning techniques, Computer Vision and NLP. The candidate should be able to develop the solution from scratch with Github codes exposed.
6. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library.
7. Should be strong in data structures and algorithms. Should be able to do code complexity analysis/optimization for smooth delivery to production.
8. Expert level coding experience in Python.
9. Technologies: Backend - Python (Programming Language)
10. Should have the ability to think long term solutions, modularity, and reusability of the components.
11. Should be able to work in a collaborative way. Should be open to learning from peers as well as constantly bring new ideas to the table.
12. Self-driven missile. Open to peer criticism, feedback and should be able to take it positively. Ready to be held accountable for the responsibilities undertaken.
Deep LearningData ScienceDeep LearningMachine Learning (ML)Python
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