Senior Machine Learning Engineer

MISSION:

HyperVerge is a fast-growing AI company started by IITians with presence in Palo Alto, Irving, Bangalore and Ho Chi Minh. In the last three years, our products powered more than 500 million AI-based automated ID checks in India, APAC, and Africa! Leading Consumer Lenders, Telcos, and Financial Services companies use HyperVerge’s Fintech Platform for customer onboarding, identity verification, fraud check, and other services. Our market-leading AI technology is currently ranked among the top 5 vendors in the NIST Face recognition leaderboard and is among the few companies in the world to be ISO certified for single image Passive Liveness.

As a Senior Machine Learning Engineer at HyperVerge Inc., you will be responsible to design, architect, build and maintain one or more AI products. You will be working on using cutting-edge deep learning techniques to solve real-world problems that involve extracting intelligence from images and videos. Examples of such problems include Face recognition, Bias mitigation in deep learning models, Forgery Detection in documents, Liveness and Authenticity verification, etc. You will be working end-to-end on every aspect of the Machine Learning solution, right from problem understanding and modeling to optimizing for accuracy and performance.

OUTCOMES EXPECTED:

AI Development

• Designing, architecting and developing high-quality Deep Learning models and algorithms for image/video recognition problems.
• Ensuring that best practices are followed in solving AI problems including thorough problem analysis, prior research understanding, persistent experimentation and documentation, rapid prototyping and extensive testing.
• Developing and researching novel AI architectures and techniques to solve the problem at hand.
• Building highly optimized AI training, validation, and data collection pipelines that work at a scale of 100s of millions of training examples.
• Devising benchmark datasets and protocols for thorough performance evaluation of the solution against real-world test cases. Benchmarking against competing solutions, prior research, and customer acceptance criteria wherever applicable.
• Working with the engineering team to productize the solutions and come up with effective ways of deploying deep learning models.
• Handling challenges w.r.t data requirements such as ideating the best ways of sourcing data, creating new tools for data annotation, etc. to effectively solve the AI problems.
• Filing for patents and publishing research papers at AI conferences.

Product Understanding

• Interfacing with the customer and product managers for thorough understanding of the product, use case and business objective.

Customer Success

• Assisting clients with necessary support needed for smooth understanding and testing of HyperVerge technology.
• Ensuring customer satisfaction and best-in-class performance of the developed solutions by continuously seeking feedback from customers, product teams, internal and external benchmarks.

Team Growth

• Contributing to the growth of the AI team through proactive effort on knowledge growth, process improvements, and performance enhancements on existing solutions.

PREREQUISITES:

1. Bachelors, Masters, or advance degree in Computer Science or related field from a reputed university.
2. Sound understanding of deep learning, computer vision and image processing, having a strong mathematical background in linear algebra, probability, and calculus.
3. 3+ years of hands-on industry experience working on machine learning and deep learning.
4. Prior exposure in building, measuring, and iterating on neural network architectures that effectively solve the problem.
5. Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, being proficient in Python.
6. Experience in end-to-end product/ feature development. Experience in building scalable products will be an added advantage.
7. Experience working with data teams to collect and organize the data needed for the task at hand.
8. Ability to explain the business reasons for developing the features and products.
9. Proven track record of being the primary contributor and tech owner of a critical module.
10. Mentored junior developers to help them achieve their goals and growth.
11. Hands-on experience deploying and maintaining AI models in production.
12. Good to have - Experience building and working with highly efficient distributed training approaches for deep learning models.