Responsibilities:
- Design, develop, and implement advanced generative models using cutting-edge AI technologies.
- Develop and maintain machine learning and deep learning models.
- Collaborate with data scientists and engineers to design and implement machine learning pipelines using MLOps practice for Data Preparation, Model Training/Re-Training, Deployment, Inference and Monitoring.
- Develop and Deploy scalable REST APIs to expose ML models to various business applications for online inference.
- Develop and implement Data Pipelines for curation of structured/un-structured and semi-structured data for Feature Engineering, Model Training and Batch / Online Inference.
- Conduct research and development activities to improve the performance and efficiency of generative models.
- Collaborate with cross-functional teams to integrate AI / ML models into our products and services.
- Develop and maintain technical documentation related to AI / ML projects and initiatives.
- Provide technical leadership and mentorship to team members.
- Participate in stakeholder discussions to understand the business needs and map into AI roadmap.
- Participate in code reviews to ensure the quality and performance of the AI models.
Requirements:
- 7+ years of experience in Machine Learning / Data Science Role.
- Bachelor or Master degree in computer science, Artificial Intelligence, Machine Learning, or a related field.
- Strong knowledge of machine learning, deep learning, and generative models.
- Experience in training and fine-tuning GenAI models.
- Proven experience in machine learning operations (MLOps).
- Proficiency in programming languages such as Python, Java, or C++.
- Familiarity with cloud platforms like AWS, Google Cloud, or Azure.
- Strong knowledge of Databricks.
- Strong knowledge of PySpark & SQL.
- Strong experience in Python web framework like Flask, Django, FastAPI.
