ML Engineer

Responsibilities:

- Collaborate with cross-functional teams to identify opportunities for technology process improvements that can be solved using machine learning and generative AI.

- Define and build innovate ML and Generative AI systems such as AI Assistants for varied SDLC tasks, and improve Data & Infrastructure management etc.

- Design and develop ML Engineering Solutions, generative AI Applications & Fine-Tuning Large Language Models (LLMs) for above ensuring scalability, efficiency, and maintainability of such solutions.

- Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs.

Requirements:

- A Master's or Ph.D. degree in Computer Science, Statistics, Data Science, or a related field.

- Proven experience working as a Software Engineer, with a focus on ML Engineering and exposure to Generative AI Applications such as chatGPT.

- Strong proficiency in programming languages such as Java, Scala, Python, Google Cloud, Biq Query, Hadoop & Spark etc

- Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies.

- Familiarity with large language models (LLMs), prompt engineering techniques, vector DB's, embedding & various fine-tuning techniques.