Machine Learning Engineer - Generative AI (4-10 yrs)

Roles and responsibilities :

- Collaborate with cross-functional teams such as Product Partners and Partner Team

- Developers to identify opportunities for process improvements that can be solved using machine learning and generative AI.

- Design, develop, and deploy machine learning models and algorithms for various business applications.

- Work on data preprocessing, feature engineering, model selection, and performance evaluation.

- Optimize and scale machine learning models for production, ensuring high performance, accuracy and low latency.

- Monitor and maintain machine learning pipelines, ensuring continuous improvement of deployed models.

- Contribute to the development of APIs and integration of machine learning models with production systems.

- Stay up-to-date with the latest machine learning research, tools, and techniques to continually enhance your skill set and improve solutions.

- Lead junior ML Engineers and guide them. Coordinate for product release and spread adoption among user communities

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

- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough and precise monitoring.

Experience and qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 4+ hands-on experience in machine learning and data science in a production environment.

- Strong proficiency in ML frameworks (e.g. Tensorflow, Pytorch, Scikit-learn, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java

- Experience with large language models (LLMs), Prompt Engineering Techniques, Langchain, OpenAI SDK, RAG system, Vector DB's (Mandatory).