Lead ML Engineer

What You Need To Succeed 4–6 years of proven, hands-on industry experience as a Machine Learning Engineer. Strong command of Python and SQL; experience with distributed computing frameworks like Spark or Hadoop is a significant plus. A bachelor's degree in computer science, Mathematics, Physics, Statistics, Operations Research, or a related field is preferred. Solid experience with ML infrastructure—including model deployment, evaluation, data processing, and debugging—with a track record of building scalable ML solutions from business requirements. Proficient in Applied LLMs and NLP, with experience developing solutions using frameworks such as Lang Chain, Lang Smith, and backend tools like Fast API. Hands-on experience with LLMs like GPT or Claude is highly desirable. Strong background in building, deploying, and integrating AI agents using LLMs is a big plus. Comfortable with software engineering best practices, including version control, unit/integration testing, and setting up CI/CD pipelines for reliable ML deployment. Committed to high code quality, with an emphasis on thorough code reviews and testing. Excellent communication skills, with the ability to collaborate across technical and non-technical teams and clearly present outcomes to business stakeholders.