Primary Purpose:
As a Machine Learning Engineer, you’ll work with a highly skilled and collaborative AI team focused on solving complex business problems with NLP and GenAI (multi-modal) technologies. You’ll gain hands-on experience in building production-grade systems, integrating ML pipelines, and applying cutting-edge models to real-world datasets. You’ll learn about ownership and stakeholder management, essential skills for growth – on the job. We take pride in ownership and commitment to follow through; we debate and discuss – but fully commit when a decision is taken.
You can expect to:
- Assist in designing and implementing NLP solutions to meet evolving business requirements
- Support the integration of ML models into scalable product pipelines. We encourage fast iterations and autonomous decision making to improve engineering practices and culture across the team.
- Experiment with various algorithms and approaches using libraries such as dask, torch, transformers, OpenAI, LlamaIndex, Langchain, etc.
- Write clean, maintainable Python code with a strong focus on modularity, performance, and scalability. We encourage infrastructure-level understanding of virtual machines, storage systems, etc.
- Collaborate with data scientists, architects, and engineers to evaluate approaches, conduct code reviews, and refine models. We iterate fast in understanding+development, but we don’t hold others back due to fast moving breaks.
- Help deploy and monitor AI pipelines using tools like Langfuse, CI/CD frameworks, Docker/Kubernetes
- Analyze model performance and propose optimizations for speed and reliability
- Real-world application of NLP and LLMs in enterprise settings (including image and video models)
- Productionizing AI algorithms with DevOps and CI/CD best practices
- Collaboration across cross-functional teams in a deeptech product environment. Product understanding is encouraged
- Insights into architecture, scaling, and system-level performance of AI modules, from day-one
- First-hand impact of AI on Fortune 500 business decision-making
Hard and soft skills:
Must haves:
- 3+ years of strong programming skills in Python and understanding of data structures & algorithms
- 3+ years working with Machine Learning frameworks and libraries such as spaCy, numpy, pandas, openai, transformers, langchain, llama-index, vllm/triton, llama.cpp, torch, etc.
- Applied understanding of OOP principles, software design patterns, REST APIs
- Familiarity with git, unit testing, and working in Unix/Linux environments
- 3+ experience working with SQL, NoSQL, vector databases (chromaDB, duckDB, postgres).
Good to haves:
- Prior experience with cloud platforms (preferably Azure)
- Exposure to Docker, Kubernetes and the full SDLC
- Familiarity with TDD, microservices, distributed systems, and event driven architecture.
Join us if you want:
- To work on cutting-edge technology in AI and NLP
- To be a part of a high-performance, high-energy and highly ambitious team
- To keep pace with the latest happenings in the AI community
- A company that focuses on your career progression
- First-hand experience on the transformation impact of AI on business insights and market research
- Peek into minds of leaders of Fortune 500 companies
- Experience work autonomy, ownership, and trust
