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.
- Stay abreast of the latest advancements in the field of Generative AI and actively contribute to the research and development of new ML & Generative AI Solutions.
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.
- Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders.
- Proven ability to adapt and learn new technologies and frameworks quickly.
- A proactive mindset with a passion for continuous learning and research in the field of Generative AI.
Bachelor's degree in Computer Science