Bristol Myers Squibb
SoftwareEngineerII-AIML
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer II - AIML at Bristol Myers Squibb. Skills: Generative AI, large language models (LLMs), Agentic AI systems, machine learning models, Python, LangChain, LangGraph, Pydantic AI. Develop Generative AI solutions leveraging large language models (LLMs) for enterprise applications including text generation, summarization, RAG (Retrieval-Augmented Generation), and intelligent assistants. Implement Agentic AI systems using multi-agent frameworks to automate complex workflows and decisi”
Industry & Context.
ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function
What They're Looking For.
Must Have
4+ years of progressively responsible experience in an IT technical role, Experience in developing and deploying ML solutions using core libraries and frameworks including Scikit-learn, NumPy, Pandas, PyTorch, TensorFlow/Keras etc, Experience working on GenAI & Agentic Frameworks like LangChain, LangGraph, Pydantic AI, LlamaIndex etc, Familiarity with LLM platforms like Azure OpenAI, AWS Bedrock, Google Vertex AI etc
Nice to Have
Develop and manage data pipelines, ML workflows, and AI applications on the Databricks platform, Build or contribute to internal AI-powered web applications using ReactJS
What You'll Do.
Develop Generative AI solutions leveraging large language models (LLMs) for enterprise applications including text generation
RAG (Retrieval-Augmented Generation)
and intelligent assistants
Implement Agentic AI systems using multi-agent frameworks to automate complex workflows and decision-making pipeline
and deploy machine learning models for classification
and other AI use cases
Build and maintain AI pipelines from data ingestion through model inference and serving
Leverage evaluation tools and platforms (e.g.
production-ready code in Python
Build AI applications using frameworks and libraries including: LangChain and LangGraph for orchestration and agentic workflows
Pydantic AI for structured data validation and AI model integration
Use VS Code or similar IDEs and leverage AI coding tools such as GitHub Copilot
and similar assistants to accelerate development productivity
and CI/CD workflows using GitHub
Collaborate with team members following Agile/Scrum methodologies
How You'll Work.
Team & Collaboration
Collaborate with team members following Agile/Scrum methodologies
Process & Methodology
Agile/Scrum methodologies
Full Job Description
**Working with Us** Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: [careers.bms.com/working-with-us](https://careers.bms.com/working-with-us). **_Responsibilities_** * Develop Generative AI solutions leveraging large language models (LLMs) for enterprise applications including text generation, summarization, RAG (Retrieval-Augmented Generation), and intelligent assistants * Implement Agentic AI systems using multi-agent frameworks to automate complex workflows and decision-making pipeline. * Design, build, and deploy machine learning models for classification, regression, NLP, and other AI use cases Build and maintain AI pipelines from data ingestion through model inference and serving * Leverage evaluation tools and platforms (e.g., LangSmith, MLflow, Weights & Biases, or equivalent) * Write clean, scalable, production-ready code in Python * Build AI applications using frameworks and libraries including: LangChain and LangGraph for orchestration and agentic workflows, Pydantic AI for structured data validation and AI model integration * Use VS Code or similar IDEs and leverage AI coding tools such as GitHub Copilot, Claude Code, and similar assistants to accelera
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