Job Description

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 an Engineering Manager - AI at HyperVerge Inc., you will be responsible to design, architect, develop, maintain and fully own one or more AI products in Computer Vision and NLP. 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 Forgery Detection in documents, Liveness, and Authenticity verification, Change detection and Infrastructure Mapping from Satellite Imagery, etc. You will be working end-to-end on every aspect of the Machine Learning solution, right from problem understanding and modelling to optimising for accuracy and performance.

OUTCOMES EXPECTED:

1. Problem Understanding:

• Interfacing with the customer, business team members and other relevant people for thorough understanding of the problem and use case, detailed specification of the requirement, understanding of the success criterion of the project, demonstration of the solution and clarification of queries at appropriate times during the lifecycle of the projects

2. Development:

• 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.
• 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.

3. Delivery and Customer Success:

• Assisting clients with necessary remote and on-site 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 and internal and external tests and benchmarks

4. Thought leadership

• Develop deep expertise in the domain to be considered as a trusted advisor by clients. Broadcast thought leadership content to inform and educate existing and potential clients

5. Team Growth & Accountability

• Deliver on the overall outcome expected of the projects
• Identify hiring needs and own the hiring end to end. Build a team of A players
• Create a clear scorecard for every person in the team, review progress periodically. Course correct, guide and coach each team member to achieve their goals.
• Manage and mentor junior developers and review periodically to help them achieve their goals and growth using ML team's structured training process
• Proactively anchor initiatives for the team which will help with one of the major challenges along the lines of recruitment, building annotation tools, competence building, onboarding, setting up supporting teams such as data, QC, et

Requirements

• Bachelors with 7+ years of hands-on industry experience working on machine learning and deep learning OR MS/PhD with 4+ years of experience, in Computer Science or related field from a reputed university
• 2+ years in a people management role. Having experience of building and managing an AI engineering team is a must.
• Sound understanding of Deep Learning, Computer Vision and Image Processing, Natural Language Processing, having a strong mathematical background in linear algebra, probability, and calculus.
• Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, being proficient in Python
• Adept at modelling the problem into a Deep Learning framework. Prior exposure in building, measuring and iterating on neural network architectures that effectively solve the problem
• Experience working with data teams to collect and organize the data needed for the task at hand.
• Experience working in a product-based startup environment will be an added advantage
• Good to have - Experience building and working with highly efficient distributed training approaches for deep learning models.