Staff AI/ML Engineer, Applied AI
Thermo Fisher Scientific2 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead the AI/ML lifecycle from ideation, research, data engineering, and model development through evaluation, tuning, deployment, and customer feedback.
- Develop, deploy, and scale AI/ML models and solutions across life sciences, genomics, materials science, and healthcare.
- Define reference architectures, software design standards, reusable patterns, and best practices for AI and Generative AI solutions.
- Establish rigorous, evaluation-driven practices for AI/ML solution development across the organization.
- Build LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
- Architect and implement agentic AI and RAG workflows involving ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering.
- Develop and integrate Generative AI systems using LangChain and LangGraph.
- Integrate AI capabilities into enterprise platforms, scientific applications, and end-to-end workflows.
- Mentor engineers and influence engineering standards, platform strategy, and AI adoption.
- Communicate architectures and technical decisions through documentation, diagrams, and design reviews.
Requirements
- Master’s degree in AI/ML, computer science, statistics, engineering, or a related technical field; Ph.D. preferred.
- 10+ years of industry experience in software engineering and developing AI/ML solutions, including production deployments beyond offline analyses or prototypes.
- 5+ years of experience working in Agile/Scrum environments.
- Hands-on experience with deep learning, CNNs, decision trees, clustering, ensembles, and related AI techniques and algorithms in production systems.
- Strong proficiency in Python, PyTorch, C++, C#, and other relevant programming languages and frameworks.
- Strong data engineering skills involving ETL, data pipelines, and large-scale processing with Pandas and NumPy.
- Production experience developing RAG and agentic AI solutions, including embeddings, retrieval, vector search, tool calling, prompt engineering, orchestration, and evaluation.
- Experience with LangChain and LangGraph for LLM orchestration and agentic workflows.
- Experience using AI coding assistants or agents in engineering workflows.
- Experience collaborating with backend, platform, and application engineers on model serving, pipeline architecture, deployment infrastructure, and production integration.
- Experience mentoring and supervising people, with strong written and verbal communication skills.
- Preferred experience applying AI/ML in life sciences, genomics, materials science, healthcare, regulatory settings, or computational biology.
- Preferred experience with MLOps or LLMOps, including deployment, monitoring, orchestration, observability, and model lifecycle management.
- Preferred experience with Azure, AWS, or GCP.
Benefits
- Standard Monday-Friday work schedule in an office 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.