Overview
Senior Consultant in AI/ML Engineering based in Bangalore, designing, building and shipping Generative AI, agentic and machine learning solutions for commercial use cases, and 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.
- Recent hands-on experience (typically 1+ years) 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).
- Fluent English.
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.
Details
- Location: Bangalore, India.
- Work mode: on average a minimum of three days per week from the office.
Read the full description and apply on the company’s own careers page.