Senior Machine Learning / LLM Engineer

We are looking for a senior engineer ( 7+ Years) who can blend deep machine learning expertise with hands-on experience in generative AI systems. This role is ideal for someone who not only builds advanced models but also drives the engineering team with clear technical direction, ensuring AI products deliver measurable business value from day one.

What You’ll Do

• Build next-gen LLM solutions

  : Design, fine-tune, and deploy large language model–based systems using advanced techniques such as prompt engineering, retrieval-augmented generation (RAG), and agent frameworks.

• Take ownership of the codebase

  : Deliver production-grade, reusable, and scalable code in Python and SQL, leveraging libraries like LangChain and LangGraph.

• Cloud deployment

  : Architect and optimize deployment pipelines on cloud platforms (Azure, AWS, or GCP), making sure CI/CD, scalability, and cost-efficiency are always considered.

• Collaborate across functions

  : Translate complex technical concepts into actionable insights for product owners, data scientists, and domain SMEs.

• Lead and mentor

  : Provide technical leadership, coach junior team members, and foster a culture of best practices in machine learning and LLM engineering.

• Stay ahead of the curve

  : Continuously experiment with new research, tools, and methods in generative AI to keep our solutions cutting-edge.

What We’re Looking For

• 5+ years of professional experience in developing and deploying ML models in production environments.
• At least 1 year of practical experience working with large language models and generative AI, including prompt design, RAG pipelines, and AI agents.
• Proven ability to set and guide a technical roadmap for engineering teams.
• Advanced programming proficiency in

  Python

  and

  SQL

  with strong expertise in LangChain/LangGraph.
• Familiarity with cloud ecosystems (Azure, AWS, or GCP) and modern DevOps practices.
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.