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.