Proactively fetches information from various sources and analyzes it for a better understanding of how the business performs, and to build AI tools that automate certain processes within the company.
Roles & Responsibilities
- Develop novel computer vision/NLP algorithms
- Build large datasets that will be used to train the models
- Empirically evaluate related research works
- Train and evaluate deep learning architectures on multiple large scale datasets
- Collaborate with the rest of the research team to produce high quality research
- Manage a team of 2+ interns
Must-have skills
- 2+years of experience in building deep learning models
- Strong basics around probability and statistics, linear algebra, data structure & algorithms
- Good knowledge of classic ML algorithms (regression, SVM, PCA etc.), deep learning
- Strong programming skills
Nice to have skills
- Familiarity with pytorch
- Knowledge of SOTA techniques in NLP and Vision
Benefits
- High level of responsibility and ownership for a product impacting billions of lives.
- Extremely high-quality talent to work with. Work with a global team between US / India.
- Work from anywhere anytime!
- Best of breed industry benefits packages.
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with the engineering team to strategize and execute the development of data products
● Execute analytical experiments methodically to help solve various problems and make a true impact across
various domains and industries
NLP ENGINEER at KARZA TECHNOLOGIES
● Identify relevant data sources and sets to mine for client business needs, and collect large structured and
unstructured datasets and variables
● Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve
models, and clean and validate data for uniformity and accuracy
● Analyze data for trends and patterns, and Interpret data with a clear objective in mind
● Implement analytical models into production by collaborating with software developers and machine
learning engineers
● Communicate analytic solutions to stakeholders and implement improvements as needed to operational
systems
What you need to work with us:
● Good understanding of data structures, algorithms, and the first principles of mathematics.
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
analyses
● Should be comfortable in going through open-source code and reading research papers.
● Should be curious or thoughtful enough to answer the “WHYs” pertaining to the most cherished
observations, thumb rules, and ideas across the data science community.
Qualification and Experience Required:
● 1 - 4 years of relevant experience
● Bachelor/ Master’s degree in computer science / Computer Engineering / Information Technology
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
analyses
● Should be comfortable in going through open-source code and reading research papers.
- B.E Computer Science or equivalent.
- In-depth knowledge of machine learning algorithms and their applications including
practical experience with and theoretical understanding of algorithms for classification,
regression and clustering.
- Hands-on experience in computer vision and deep learning projects to solve real world
problems involving vision tasks such as object detection, Object tracking, instance
segmentation, activity detection, depth estimation, optical flow, multi-view geometry,
domain adaptation etc.
- Strong understanding of modern and traditional Computer Vision Algorithms.
- Experience in one of the Deep Learning Frameworks / Networks: PyTorch, TensorFlow,
Darknet (YOLO v4 v5), U-Net, Mask R-CNN, EfficientDet, BERT etc.
- Proficiency with CNN architectures such as ResNet, VGG, UNet, MobileNet, pix2pix,
and Cycle GAN.
- Experienced user of libraries such as OpenCV, scikit-learn, matplotlib and pandas.
- Ability to transform research articles into working solutions to solve real-world problems.
- High proficiency in Python programming knowledge.
- Familiar with software development practices/pipelines (DevOps- Kubernetes, docker
containers, CI/CD tools).
- Strong communication skills.
DATA 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
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.
- 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!
- Passionate about search & AI technologies. Open to collaborating with colleagues & external contributors.
- Good understanding of the mainstream deep learning models from multiple domains: computer vision, NLP, reinforcement learning, model optimization, etc.
- Hands-on experience on deep learning frameworks, e.g. Tensorflow, Pytorch, MXNet, BERT. Able to implement the latest DL model using existing API, open-source libraries in a short time.
- Hands-on experience with the Cloud-Native techniques. Good understanding of web services and modern software technologies.
- Maintained/contributed machine learning projects, familiar with the agile software development process, CICD workflow, ticket management, code-review, version control, etc.
- Skilled in the following programming languages: Python 3.
- Good English skills especially for writing and reading documentation
- Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
- Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”.
- Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with data scientists to understand and implement machine learning algorithms.
- Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models.
- Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
- Mentor junior team members
Who we have in mind:
- Graduate in Computer Science or related field, or equivalent practical experience.
- 4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
- Proficiency with SQL, Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
- Familiarity with deep learning frameworks such as TensorFlow or Keras
- Experience with Computer Vision (OpenCV), NLP frameworks (NLTK, SpaCY, BERT).
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Understand machine learning principles (training, validation, etc.)
- Strong hands-on knowledge of data query and data processing tools (i.e. SQL)
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Experience deploying highly scalable software supporting millions or more users
- Experience building applications on cloud (AWS or Azure)
- Experience working in scrum teams with Agile tools like JIRA
- Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users
About the Company
- 💰 Early-stage, ed-tech, funded, growing, growing fast.
- 🎯 Mission Driven: Make Indonesia competitive on a global scale.
- 🥅 Build the best educational content and technology to advance STEM education
- 🥇 Students-First approach
About the People
- ❤️ Love what we do
- 🎮 Committed to making learning fun, accessible, and safe
- 🤝 Teams are better. We value ownership, responsibility, transparency
- 🌏 Global, diverse backgrounds. Been there, done that.
What does it look like one year from now?
- CoLearn has grown so much, and you’ve been an important part of the growth. You solved hard problems that many didn’t know existed.
- You’ve led the data science function and laid out the roadmap, implemented best practices, and grown the team. You’ve executed mission-critical projects. Congratulations!
- You’re exploring what Data Science can do for the students, parents, teachers, educators.
- You’ve been speaking at Data Science conferences about the image recognition system we built from scratch. You casually threw in the semantic search engine on slide 77.
- The engineering and product teams are your friends. The teams take cross-functional collaboration, testing, and modeling for granted. It’s their second nature.
- You have an encyclopedic knowledge of CoLearn’s data structures and metrics, and you’ve often provided key ideas for the product.
About you
- Highly-skilled and experienced Data Scientist and leader
- You are interested in creating next-gen data-powered education tech products.
- You’ve worked in a Data Science role before where you took a data product to market
- You are comfortable working with unknowns, evaluating the data, and applying scientific techniques to business problems and products
- You’ve built platforms and systems from scratch
- You have a track record of developing and deploying data-science models to production
Let’s talk tech
- End-to-end AI/ML systems in the cloud, including data processing, feature engineering, and tuning of ML models in training and production (MLOps) — with both structured and unstructured data.
- Deep Learning and Computer Vision models, ideally in a production environment
- Hands-on Python/SQL, scikit-learn, Keras, PyTorch, Tensorflow, MXnet, etc.
- Experience in Scala/Java/Go/C/C++ is a plus plus
- Airflow/Luigi/Oozie and the likes
- Familiarity with cloud deployment strategies (AWS/GCP) to deploy at scale
Track record
- B.S./B.E./M.S./PhD in a quantitative field such as Computer Science, Engineering, Math, Statistics or equivalent years of experience
- 10+ years of experience in data science, algorithmic engineering, and machine learning. Preferably solved problems from scratch to scale
- Experience in hiring, managing highly-performant teams, and mentoring data science, data engineering, and analytics teams
- Experience developing a data science strategy, building the roadmap, and leading the execution
- Track record of recruiting talent in analytics and data science
You will make us go 😍 if:
- You’ve won algorithm and machine learning competitions such as ACM and Kaggle
- You have research publications and citations in top tier journals
- You have a portfolio of side projects and can show it to us
Glance – An InMobi Group Company:
Glance is an AI-first Screen Zero content discovery platform, and it’s scaled massively in the last few months to one of the largest platforms in India. Glance is a lock-screen first mobile content platform set up within InMobi. The average mobile phone user unlocks their phone >150 times a day. Glance aims to be there, providing visually rich, easy to consume content to entertain and inform mobile users - one unlock at a time. Glance is live on more than 80 millions of mobile phones in India already, and we are only getting started on this journey! We are now into phase 2 of the Glance story - we are going global!
Roposo is part of the Glance family. It is a short video entertainment platform. All the videos created here are user generated (via upload or Roposo creation tools in camera) and there are many communities creating these videos on various themes we call channels. Around 4 million videos are created every month on Roposo and power Roposo channels, some of the channels are - HaHa TV (for comedy videos), News, Beats (for singing/ dance performances) along with a For You (personalized for a user) and Your Feed (for videos of people a user follows).
What’s the Glance family like?
Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. Glanciers are passionate and driven, creative and fun-loving, take ownership and are results-focused. We invite you to free yourself, dream big and chase your passion.
What can we promise?
We offer an opportunity to have an immediate impact on the company and our products. The work that you shall do will be mission critical for Glance and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At Glance, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.
What you will be doing?
Glance is looking for a Data Scientist who will design and develop processes and systems to analyze high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors. Interacts with business partners to identify questions for data analysis and experiments. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and or prepares output from analysis and experiments to business partners.
You will be working with Product leadership, taking high-level objectives and developing solutions that fulfil these requirements. Stakeholder management across Eng, Product and Business teams will be required.
Basic Qualifications:
- Five+ years experience working in a Data Science role
- Extensive experience developing and deploying ML models in real world environments
- Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
- Exceptional familiarity with Python, Java, Spark or other open-source software with data science libraries
- Experience in advanced math and statistics
- Excellent familiarity with command line linux environment
- Able to understand various data structures and common methods in data transformation
- Experience deploying machine learning models and measuring their impact
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Preferred Qualifications
- Experience developing recommendation systems
- Experience developing and deploying deep learning models
- Bachelor’s or Master's Degree or PhD that included coursework in statistics, machine learning or data analysis
- Five+ years experience working with Hadoop, a NoSQL Database or other big data infrastructure
- Experience with being actively engaged in data science or other research-oriented position
- You would be comfortable collaborating with cross-functional teams.
- Active personal GitHub account.
We are looking for applicants with a strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning and Pattern Recognition, Natural Language Processing and Computational Linguistics, Statistical Modelling and Inferencing, Information Retrieval, Large Scale Distributed Systems and Cloud Computing, Econometrics and Quantitative Marketing, Applied Game Theory and Mechanism Design, Operations Research and Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply.
We are looking for someone who can create and implement AI solutions. If you have built a product like IBM WATSON in the past and not just used WATSON to build applications, this could be the perfect role for you.
All successful candidates are expected to dive deep into problem areas of Zycus’ interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization.
Skills:
- Experience in predictive modelling and predictive software development
- Skilled in Java, C++, Perl/Python (or similar scripting language)
- Experience in using R, Matlab, or any other statistical software
- Experience in mentoring junior team members, and guiding them on machine learning and data modelling applications
- Strong communication and data presentation skills
- Classification (svm, decision tree, random forest, neural network)
- Regression (linear, polynomial, logistic, etc)
- Classical Optimization(gradient descent, newton raphson, etc)
- Graph theory (network analytics)
- Heuristic optimisation (genetic algorithm, swarm theory)
- Deep learning (lstm, convolutional nn, recurrent nn)
Must Have:
- Experience: 3-9 years
- The ideal candidate must have proven expertise in Artificial Intelligence (including deep learning algorithms), Machine Learning and/or NLP
- The candidate must also have expertise in programming traditional machine learning algorithms, algorithm design & usage
- Preferred experience with large data sets & distributed computing in Hadoop ecosystem
- Fluency with databases