Sr AI/ML Engineer, Applied AI

Thermo Fisher Scientific Inc.; Índia; Presencial; INR 2 500 000 - 5 200 000; Tempo integral

Resumo da oferta

Thermo Fisher Scientific Inc. is hiring a senior AI/ML engineer to lead end-to-end AI initiatives in India. You will guide model development, deployment, and governance across life sciences, genomics, and healthcare domains, translating complex data into scalable solutions.

The role emphasizes collaboration with backend teams, stakeholder communication, and ongoing learning to apply Generative AI advancements in enterprise platforms and scientific workflows.

Qualificações

• Bachelor's degree in AI/ML, CS, statistics, engineering or related field; Master's preferred.
• 6+ years of industry experience in software engineering and AI/ML production solutions.
• 4+ years in agile/scrum environments.
• Hands-on experience with deep learning, CNNs, decision trees, clustering and ensembles.
• Hands-on experience with retrieval-augmented generation (RAG) and agentic AI solutions.
• Strong proficiency in Python, PyTorch, C++, C# and related languages.
• Experience with LangChain and LangGraph for LLM orchestration.
• Strong data engineering skills: ETL pipelines, Pandas, NumPy.
• Ability to collaborate with backend teams for deployment and production integration.
• Proven experience using AI coding assistants or agents in engineering workflows.
• Excellent written and verbal communication; adaptable in fast-paced environments.
• Preferred: life sciences/genomics/healthcare experience; MLOps/LLMOps; cloud platforms.

Responsabilidades

• Lead activities across the AI/ML lifecycle—from ideation to deployment with customer feedback.
• Iteratively develop, deploy and scale AI/ML models across life sciences and healthcare domains.
• Contribute to AI/GenAI models following architectures, standards and best practices.
• Apply evaluation-driven approaches with evaluation frameworks and performance analysis.
• Build and deploy LLM-powered services using Azure OpenAI, Claude and OpenAI APIs.
• Architect and implement agentic AI and RAG workflows: ingestion, embeddings, vector search, tool calling, memory, prompts.
• Design and integrate Generative AI systems using LangChain and LangGraph for orchestration.
• Integrate AI capabilities into enterprise platforms and scientific workflows.
• Mentor engineers across the AI/ML lifecycle and participate in Communities of Practice.
• Communicate with stakeholders via documentation, diagrams and reviews.
• Stay current with AI/ML advances and apply innovations to internal tools and customer products.

Conhecimentos

Python

PyTorch

C++

C#

LangChain

LangGraph

ETL/Data pipelines

Pandas/NumPy

LLM orchestration

RAG workflows

Formação académica

Bachelor's degree in AI/ML, CS, stats, eng

Master's degree preferred

Ferramentas

Azure OpenAI

Anthropic Claude

OpenAI APIs

Descrição da oferta de emprego

About The Role

At Thermo Fisher Scientific, you’ll do meaningful work that makes a positive global impact. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner, and safer. With industry-leading R&D investment, we empower our teams to solve complex scientific challenges—from environmental protection to advancing healthcare and cancer research.

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Key Responsibilities

• Lead activities across the AI/ML lifecycle – from ideation, research, data engineering, model development and optimization, evaluation, performance tuning and deployment, while continuously engaging customers to gather feedback and incorporate it into solution development.
• Iteratively develop, deploy and scale AI/ML models and solutions across life sciences, genomics, material sciences, and healthcare.
• Contribute to the development of AI/ML models and solutions, following established model and system architectures, software design standards, reusable patterns, and best practices for AI and Generative AI solutions.
• Apply evaluation-driven approaches to AI/ML development by implementing and running evaluation frameworks, analyzing model performance, and using results to improve the quality and reliability of AI/ML solutions.
• Build and deploy LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
• Architect and implement agentic AI and RAG workflows, including data ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering.
• Design, develop, and integrate Generative AI systems using LangChain and LangGraph for agentic workflows and orchestration.
• Integrate AI/Generative AI capabilities into enterprise platforms, scientific applications and end-to-end workflows.
• Mentor and guide engineers across the AI/ML lifecycle, including model development, evaluation, and implementation of AI solutions.
• Actively participate in Communities of Practice, influencing engineering standards and AI/Generative AI adoption strategies across the organization.
• Communicate effectively with technical and non-technical stakeholders through clear documentation, architecture diagrams and design reviews.
• Stay current with advancements in AI/ML, Generative AI, agentic frameworks, and LLM ecosystems, and apply relevant innovations to enhance internal tools, scientific solutions and customer-facing products.

Candidate Requirement

Education and Experience:

• Bachelor’s degree in AI/ML, computer science, statistics, engineering, or a related technical field. Master’s. degree preferred.
• 6+ years of industry experience in software engineering and developing AI/ML solutions, with a strong track record of shipping these into real production systems in a robust experimentation framework, not just offline analyses or research prototypes.
• 4+ years of experience working in agile/scrum environments.
• Hands‑on experience in developing and applying AI techniques and algorithms, including deep learning, CNNs, decision trees, clustering, ensembles, and related approaches.
• Hands‑on experience developing retrieval‑augmented generation (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 with backend engineering best practices, with demonstrated ability to design, build and own reliable, scalable systems that serve users.
• Experience with LangChain and LangGraph for LLM orchestration and agentic workflows.
• Strong data engineering skills, including ETL/data pipelines and large‑scale data processing and analysis using tools such as Pandas and NumPy.
• Ability to work closely with backend, platform, and application engineers on model serving, pipeline architecture, deployment infrastructure, and production integration with sound judgement in balancing scope, quality, and speed to delivery.
• Demonstrated experience leveraging AI coding assistants or agents as part of your engineering workflow.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly.
• Flexibility and adaptability to work in a fast‑paced and collaborative environment.
• Preferred: Hands‑on experience developing and deploying AI/ML models and solutions for life sciences, genomics, materials sciences, healthcare, or other regulatory settings.
• Preferred: Experience with MLOps or LLMOps concepts including deployment, monitoring, orchestration, observability, and model lifecycle management.
• Nice‑to‑have: Experience applying AI/ML models and methods to computational biology.
• Nice‑to‑have: Experience with cloud platforms such as Azure, AWS or GCP.