- ML Pipelines & Experimentation: Support Data scientists and data engineers by ensuring production ready data, model pipelines are deployed to production.
- Manage the entire model lifecycle using the code frameworks developed by AI Platform team for feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality.
- Establish and promote best practices in MLOps to streamline model deployment and monitoring across various environments
- Provide authoritative guidance on state-of-the-art algorithms, repositories, and GenAI techniques like prompt engineering, RAG, AI agents in Generative AI space (LLMs) & share your experience with optimisation techniques such as quantization, pruning, to minimise training & inference requirements for models.
- Design and implement effective LLM-tooling, finetuning & response evaluation strategies.
- Guide teams on the latest AI solution development practices and capabilities, and accordingly refine and improve our model development lifecycle and disseminate best practice learnings to colleagues.
- Help refine and extend our standards and best practices around Machine Learning – training and testing framework, coding standards, engineering practices.
- Demonstrate a strong understanding of natural language processing methods, including deep learning techniques, knowledge distillation, prompt engineering, and fine-tuning.
- 5-8 years of Industry experience with minimum 2 years of experience working in AWS & AWS Sagemaker and developing Sagemaker pipelines
- Knowledge of Jenkins, CloudFormation, terraform code & MLOps practices
- Exhibit proficiency in Python, software engineering practices, along with expertise in deep learning frameworks (ML/distributed ML frameworks like TensorFlow etc)
- Possess outstanding communication skills and the ability to collaborate effectively with interdisciplinary teams.
- Proven experience in the full ML model development lifecycle, including design, deployment, and maintenance.
- Demonstrated experience with Generative AI technologies and LLMOps practices including in AI Agents and ideally in Agentic frameworks
- Ability to work collaboratively in a fast-paced, innovative environment.
- Strong problem-solving skills and a passion for implementing cutting-edge AI solutions.
- Proficient coding skills and strong software development experience (Spark, Python)
- Bachelors/Masters or PhD program in Computer Science/Statistics or a related field
TBD