Ml Engineer

Job Description

Required skills 5+ years of professional experience in building Machine Learning models & systems 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents. Experience in driving the engineering team toward a technical roadmap. Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must. Understanding of Cloud services, including Azure, GCP, or AWS Excellent communication skills to effectively collaborate with business SMEs Roles & Responsibilities Develop and optimize LLM-based solutions : Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures. Codebase ownership : Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices. Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes. Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products. Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development. Continuous innovation : Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.