Position : Lead AI/ML Engineer

Qualifications :

- Overall 8+ years of work experience as a Machine Learning Engineer or related role, with min. 3+ years as a team lead.

- Strong coding experience in Python is required.

- More than 4+ years of experience with designing and developing popular, highly scalable, distributed ML models and open-source projects.

- Contribution towards multiple use cases.

- Understanding of data structures, data modelling and software architecture.

- Familiarity and proficiency with machine learning frameworks (like PyTorch, TensorFlow, Keras, MxNet) and libraries (like scikit-learn, pandas).

- Knowledge of CUDA, OpenCL.

- Understanding and scripting on SQL/ NoSQL databases (e.g., MySQL, MangoDB).

- Familiarity with various operating systems (e.g., Windows, UNIX/Linux, Ubuntu).

- Knowledge in other programming languages like Java, .net, JavaScript is an added advantage.

- Knowledge on deployment of the ML models on any cloud-based platforms (AWS, Azure, GCP).

- Knowledge on Big Data & tools like Spark based distributed training and inferencing.

- Reinforcement Learning, Neural Networks and Natural Language Processing knowledge on packages like NLTK, Gensim, SpaCy, CoreNLP is a bonus.

- Knowledge of text detection, generative models, reinforcement learning, model compression / optimization.

- Deep and profound knowledge of math, probability, statistics, and algorithms.

- Should have led a team of engineers towards deployment of projects.

- Outstanding analytical and problem-solving skills.

- Good team player and excellent written and verbal technical communication skills.

- Preferable to have FMCG/CPG domain knowledge.

- BE / BCA / BSc in Computer Science; Masters degree in the same stream is a plus.

Responsibilities :

- Deliver robust, well-tested, and fully documented modules to serve the use cases.

- Collaborate with Product Management and proactively provide inputs during new use case/feature/module development or connects with project teams.

- Act as an anchor to lead the developments from technical front.

- Design and work with engineering team to implement the entire application modules as discoverable microservices, experience hosting and deploying ML solutions.

- Collaborate with Product teams, system architects, designers, and engineers to support the development of robust machine learning systems.

- Continuously improve the efficiency, robustness, and cost of existing modules.

- Assess and recommend technology choices and directions in consideration of cost-benefit trade-offs.

- Build engineering plans, and schedule estimates.

- Perform code reviews and ensure proper design and delivery.

- Promote best practices and establishing team processes.

- Identify infrastructure and architectural investment needs.

- Hire, develop, and lead an inclusive, engaged, and high performing team.