Responsibilities

- Lead applied research in LLMs, generative AI, and multimodal models.
- Evaluate and experiment with state-of-the-art architectures (e.g., Transformers, Diffusion Models, Retrieval-Augmented Generation).
- Publish internal whitepapers and contribute to external conferences where applicable.
- Design and implement scalable AIML pipelines using frameworks like PyTorch, TensorFlow, Hugging Face, and MLflow.
- Collaborate with engineering teams to deploy models into production using MLOps best practices (CI/CD, model versioning, monitoring).
- Evaluate and integrate advanced AIML tools such as GitHub Copilot, Windsurf, Vertex AI, Azure OpenAI, and Hugging Face Transformers.
- Work with cloud platforms (AWS, Azure, GCP) to ensure scalable and secure model deployment.
- Architect end-to-end AIML systems including data ingestion, model training, inference, and feedback loops.




- Mentor junior engineers and researchers.
- Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders.

Qualifications
- Undergraduate degree or equivalent experience.
- Bachelor's or relevant in Computer Science, Machine Learning, or related field.
- 4+ years of experience in AIML engineering and research.
- Proven expertise in LLMs, generative AI, and deep learning.
- Robust programming skills in Python and familiarity with ML libraries (e.g., scikit-learn, Keras).
- Experience with experiment tracking tools (e.g., Weights & Biases, MLflow).
- Hands-on experience with MLOps, model deployment, and monitoring.
- Familiarity with AIML governance, ethics, and responsible AI practices.

📌 AI/ML Engineer (Bengaluru)
🏢 Optum
📍 Bengaluru