AI/ML Platform Engineer
About The Position
We are looking for a hands-on AI/ML Platform Engineer to support the implementation and operation of scalable platforms for Generative AI, LLMOps, and MLOps in a pharmaceutical environment. This role involves close collaboration with data scientists, engineers, and business partners to operationalize AI workflows, integrate various technologies including Cloud services, build reusable infrastructure components and promote adoption of standards and best practices. You will work with tools like DataIKU, Snowflake Cortex, Azure AI Services, AWS AI Services, and contribute to agentic and prompt-driven AI solutions.
Requirements
- 2–5 years in DevOps, ML engineering, or platform development roles.
- Experience with cloud-based AI services on Azure (OpenAI, ML) and/or AWS (SageMaker, Bedrock, Comprehend, etc.).
- Skilled in Python and familiar with frameworks such as FastAPI or Flask.
- Hands-on with DataIKU for workflow orchestration and project automation.
- Working knowledge of containerization (Docker), CI/CD tools, and vector database integrations.
- Strong collaboration skills and the ability to work closely with data scientists, engineers, and business partners.
- Effective communication and problem-solving skills, with attention to delivering high-quality results.
- Self-motivated and results-oriented, with an eagerness to learn and grow in GenAI and platform engineering.
Nice To Haves
- Experience with prompt engineering and LLM prompt tuning is a plus.
- Familiarity with agentic tools like LangChain or AutoGen is preferred.
Responsibilities
- Implement AI/ML pipelines and workflows using DataIKU, Azure AI, Snowflake Cortex, and AWS AI Services.
- Support LLMOps/MLOps operations including deployment, monitoring, versioning, and CI/CD automation.
- Contribute to agentic AI workflows leveraging various technics and tools such as LangChain, LangGraph, Semantic Kernel, AutoGen.
- Assist with prompt engineering, crafting and tuning prompts for internal LLM use cases.
- Facilitate in the evaluation of LLMs for specific use case scenarios.
- Integrate APIs for model inference, embeddings, vector search, and retrieval-augmented generation.
- Automate platform setup and configuration using scripting and infrastructure-as-code tools.
- Collaborate with business stakeholders and data science teams to deploy reliable and maintainable AI components.
- Collaborate with infrastructure team to monitor deployed solutions, resolve issues, and ensure service-level reliability.
- Adopt and promote platform standards, reusable components, and best practices to improve AI solution delivery consistency.
- Follow best practices in responsible and secure AI development within regulated environments.
Benefits
- Comprehensive medical, dental, vision, prescription drug coverage, company provided basic life, accidental death & dismemberment, short-term and long-term disability insurance, tuition reimbursement, student loan assistance, a generous 401(k) match, flexible time off, paid holidays, and paid leave programs as well as other company provided benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees
