Machine Learning (ML)
Python
Deep LearningResponsibilities:
- 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.
- Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
- To design and develop Machine Learning systems and schemes.
- To perform statistical analysis and fine-tune models using test results.
- To train and retrain ML systems and models as and when necessary.
- To deploy ML models in production and maintain the cost of cloud infrastructure.
- To develop Machine Learning apps according to client and data scientist requirements.
- To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.
Technical Knowledge:
- Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase.
- Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
- Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark, Pandas, Numpy and related libraries.
- Expert in visualising and manipulating complex datasets.
- Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
- Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
- Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
- Big data Technologies such as Hadoop stack and Spark.
- Basic use of clouds (VM’s example EC2).
- Brownie points for Kubernetes and Task Queues.
- Strong written and verbal communications.
- Experience working in an Agile environment.
Subodh Popalwar
Software Engineer, Memorres
About SmartJoules
Energy efficiency is the cleanest, quickest and cheapest way to bring more than 300 million Indians out of energy poverty.
By eliminating waste in their own operations, building owners can save money, simplify operations, improve comfort and free up resources for the less fortunate. Smart Joules makes this process seamless and profitable from day one.
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2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data
3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.
5. Experience in SOTA Deep Learning techniques to solve NLP problems.
6. End-to-end data collection, model development and testing, and integration into production environments.
7. Build and prototype analysis pipelines iteratively to provide insights at scale.
8. Experience in querying different data sources
9. Partner with developers and business teams for the business-oriented decisions
10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
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Greetings from Deltacubes Technology!!
Skillset Required:
Python
Pyspark
AWS
Scala
Experience:
5+ years
Thanks
Bavithra
• Problem Solving:. Resolving production issues to fix service P1-4 issues. Problems relating to
introducing new technology, and resolving major issues in the platform and/or service.
• Software Development Concepts: Understands and is experienced with the use of a wide range of
programming concepts and is also aware of and has applied a range of algorithms.
• Commercial & Risk Awareness: Able to understand & evaluate both obvious and subtle commercial
risks, especially in relation to a programme.
Experience you would be expected to have
• Cloud: experience with one of the following cloud vendors: AWS, Azure or GCP
• GCP : Experience prefered, but learning essential.
• Big Data: Experience with Big Data methodology and technologies
• Programming : Python or Java worked with Data (ETL)
• DevOps: Understand how to work in a Dev Ops and agile way / Versioning / Automation / Defect
Management – Mandatory
• Agile methodology - knowledge of Jira
Python
Java
Javascript|
Python + Data scientist : |
|
• Build data-driven models to understand the characteristics of engineering systems |
|
• Train, tune, validate, and monitor predictive models |
|
• Sound knowledge on Statistics |
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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
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!
Machine Learning (ML)We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
Skills:
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.
Data Science
R ProgrammingPython
Data Analytics- Identifying valuable data sources and automate collection processes
- Undertaking preprocessing of structured and unstructured data
- Analyzing large amounts of information to discover trends and patterns
- Building predictive models and machine-learning algorithms
- Combining models through ensemble modeling
- Presenting information using data visualization techniques
- Proposing solutions and strategies to business challenges
- Collaborating with engineering and product development teams
What you need to have:
- Data Scientist with min 3 years of experience in Analytics or Data Science preferably in Pricing or Polymer Market
- Experience using scripting languages like Python(preferred) or R is a must.
- Experience with SQL, Tableau is good to have
- Strong numerical, problem solving and analytical aptitude
- Being able to make data based decisions
- Ability to present/communicate analytics driven insights.
- Critical and Analytical thinking skills
Python
DjangoPosition Name: Software Developer
Required Experience: 3+ Years
Number of positions: 4
Qualifications: Master’s or Bachelor s degree in Engineering, Computer Science, or equivalent (BE/BTech or MS in Computer Science).
Key Skills: Python, Django, Ngnix, Linux, Sanic, Pandas, Numpy, Snowflake, SciPy, Data Visualization, RedShift, BigData, Charting
Compensation - As per industry standards.
Joining - Immediate joining is preferrable.
Required Skills:
- Strong Experience in Python and web frameworks like Django, Tornado and/or Flask
- Experience in data analytics using standard python libraries using Pandas, NumPy, MatPlotLib
- Conversant in implementing charts using charting libraries like Highcharts, d3.js, c3.js, dc.js and data Visualization tools like Plotly, GGPlot
- Handling and using large databases and Datawarehouse technologies like MongoDB, MySQL, BigData, Snowflake, Redshift.
- Experience in building APIs, Multi-threading for tasks on Linux platform
- Exposure to finance and capital markets will be added advantage.
- Strong understanding of software design principles, algorithms, data structures, design patterns, and multithreading concepts.
- Worked on building highly-available distributed systems on cloud infrastructure or have had exposure to architectural pattern of a large, high-scale web application.
- Strong understanding of software design principles, algorithms, data structures, design patterns, and multithreading concepts.
- Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3
Company Description:
Reval Analytical Services is a fully-owned subsidiary of Virtua Research Inc. US. It is a financial services technology company focused on consensus analytics, peer analytics and Web-enabled information delivery. The Company’s unique combination of investment research experience, modeling expertise, and software development capabilities enables it to provide industry-leading financial research tools and services for investors, analysts, and corporate management.
Website: http://www.virtuaresearch.com" target="_blank">www.virtuaresearch.com
Data ScienceMachine Learning (ML)Deep Learning
Follow CutshortSubodh Popalwar
Software Engineer, Memorres