Sr AI/ML Engineer, Applied AI
Thermo Fisher Scientific2 months ago
Bengaluru, IndiaSenior
Responsibilities
- Lead the full AI/ML lifecycle from ideation and research through data engineering, model development, evaluation, optimization, deployment, scaling, and customer feedback.
- Develop and deploy AI/ML models and solutions for life sciences, genomics, materials science, healthcare, and related domains.
- Build LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
- Architect and implement RAG and agentic AI workflows involving ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, prompt engineering, and evaluation.
- Design and integrate generative AI systems using LangChain and LangGraph for agentic orchestration.
- Implement evaluation frameworks, analyze model performance, and improve the quality and reliability of AI/ML systems.
- Integrate AI and generative AI capabilities into enterprise platforms, scientific applications, and end-to-end workflows.
- Mentor engineers, contribute to Communities of Practice, and influence engineering standards and AI adoption strategies.
- Communicate technical concepts through documentation, architecture diagrams, and design reviews while collaborating with technical and non-technical stakeholders.
Requirements
- Bachelor’s degree in AI/ML, computer science, statistics, engineering, or a related technical field is required; a master’s degree is preferred.
- At least 6 years of industry experience in software engineering and developing AI/ML solutions, including shipping robust production systems.
- At least 4 years of experience working in agile/scrum environments.
- Hands-on experience with deep learning, CNNs, decision trees, clustering, ensembles, and related AI/ML techniques.
- Hands-on experience developing RAG and agentic AI solutions, including embeddings, retrieval, vector search, tool calling, prompt engineering, orchestration, and evaluation.
- Strong proficiency in Python, PyTorch, C++, C#, and other relevant programming languages and frameworks.
- Expertise in backend engineering and designing, building, and owning reliable, scalable systems serving users.
- Experience with LangChain and LangGraph for LLM orchestration and agentic workflows.
- Strong data engineering skills, including ETL, data pipelines, and large-scale processing and analysis with Pandas and NumPy.
- Experience collaborating on model serving, pipeline architecture, deployment infrastructure, and production integration.
- Experience using AI coding assistants or agents in an engineering workflow.
- Excellent written and verbal communication skills and the ability to explain complex technical concepts clearly.
- Preferred experience deploying AI/ML solutions in life sciences, genomics, materials science, healthcare, or regulated environments.
- Preferred experience with MLOps or LLMOps, including deployment, monitoring, orchestration, observability, and model lifecycle management.
- Experience applying AI/ML to computational biology and familiarity with Azure, AWS, or GCP are nice to have.
Benefits
- Standard Monday-Friday work schedule.
- Office-based work environment.
Categories
About Thermo Fisher Scientific
Thermo Fisher Scientific builds analytical instruments, lab equipment and consumables, specialty diagnostics, and provides pharma services (CDMO and clinical research) for biotech, pharma, academic, and healthcare customers. It earns revenue through product sales, e-commerce distribution (Fisher Scientific), and contract services under brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Patheon, and PPD. Headquartered in Waltham, MA, it is publicly traded on the NYSE (TMO) and was created by the 2006 merger of Thermo Electron and Fisher Scientific.