Senior Consultant, AI/ML Engineering

Overview

Design, build and ship Generative AI and agentic solutions, along with classical ML, that help clinicians, field teams and partners make faster, smarter commercial decisions, leading end-to-end delivery from problem framing through deployment and monitoring.

What you'll do

• Design, build and deploy Generative AI and agentic solutions for commercial use cases, including LLM applications and multi-agent systems on frameworks such as Amazon Bedrock AgentCore.
• Develop and apply fine-tuning and distillation techniques to enhance quality while reducing cost and latency.
• Build and operate evaluation harnesses and platforms to measure quality, safety and reliability of LLM and agent systems, using results to drive continuous improvements.
• Implement telemetry, tracing and monitoring for AI systems in production and respond to quality, drift and cost issues.
• Explore and apply reinforcement learning and feedback-based optimisation where they add measurable value.
• Develop and maintain traditional ML models (classification, regression, clustering, forecasting, NLP) for commercial analytics.
• Integrate internal and external structured and unstructured data by partnering with data engineering, informatics and platform teams.
• Lead technical workstreams and write production-quality, well-tested and well-documented code that scales.
• Collaborate with Commercial, Medical, IT and other partners to scope problems, define success metrics and deliver scalable solutions.
• Research and apply the latest algorithms and methods to business problems, and coach junior data scientists and engineers to set the standard.

What you'll need

• BS (or equivalent experience) in computer science, mathematics, statistics, engineering, physics, computational sciences or a related quantitative field.
• Typically 6+ years of experience building data science and ML solutions.
• Typically 1+ years of recent hands-on experience with LLM-based applications.
• A track record of independently leading data science or AI projects to solve business or scientific problems.
• Generative AI and LLMs: prompt and context engineering, retrieval-augmented generation, and working knowledge of fine-tuning and distillation approaches.
• Agentic AI: experience building agents or multi-agent workflows using frameworks such as Amazon Bedrock AgentCore, LangGraph, Strands or similar.
• Evaluation: experience designing and running evaluations of LLM and agent systems.
• Machine learning foundations: classical ML (supervised and unsupervised methods, including classification and regression) and deep learning, including transformers, using PyTorch or TensorFlow.
• Programming and tools: exceptional Python; SQL and familiarity with NoSQL; scikit-learn; Jupyter; Streamlit or similar.
• Cloud: working knowledge of AWS (SageMaker, Bedrock preferred).

Nice to have

• Master's or PhD in machine learning, computer science or a related field.
• Familiarity with reinforcement learning, including preference-based optimisation of LLMs.
• Experience with telemetry and observability tooling for AI systems.
• MLOps tooling: MLflow, Docker, CI/CD, and pipeline tools such as Airflow.
• Experience with knowledge graphs, and with structured and unstructured data (text and image).
• Pharmaceutical, healthcare or commercial analytics domain experience.
• Curiosity and a desire to keep learning new technologies and methods in AI.
• Ability to explain complex methods and techniques to a non-technical audience.
• Ability to collaborate closely with multi-functional, global teams.
• Good written and verbal communication skills; fluent English.

Details

• Location: Bangalore, India.
• Work mode: in-person working, on average a minimum of three days per week from the office.
• Date posted 13-Nov-2026; closing date 19-Nov-2026.