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Amgen Inc
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Principal Machine Learning Engineer

Principal Machine Learning Engineer

Amgen Inc

3 - 5 years

10 - 13 Lacs

hyderabad

Posted:4 days ago| Platform:

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Skills Required

python presentation skills containerization java troubleshooting kubernetes semantic github scaled agile framework kernel microsoft azure aiml artificial intelligence docker pipeline gcp devops vector aws ml agile methodology

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are seeking a Principal Machine Learning Engineer Amgens most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI solutions. Sitting at the intersection of engineering excellence and data-science enablement, you will develop, deploy and monitor modelsclassical ML, deep learning and LLMssecurely and cost-effectively. Acting as a player-coach, you will establish AI solution strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI solutions.

Roles & Responsibilities:

Design and ship production agentic systems: multi-agent planning, tool/function calling, workflow orchestration, and structured outputs.
Build high-containment bots for web/mobile/Slack/Teams/IVR with streaming responses and sub-second turn latency where required.
Build production ML/GenAI solutions and lightweight apps delivering sub-second insights.
Implement retrieval & memory (RAG, vector stores, knowledge graphs, session memory) with data contracts, lineage, and lifecycle governance.
Establish bot CI/CD: prompt & config versioning, replay/conversation tests, feature flags, and automated rollbacks. Implement progressive delivery (blue-green, canary) with health checks, feature flags, and one-click rollback.
Establish LLM observability , SLOs, and safe deploys (blue-green/canary, shadow, rollbacks) with incident runbooks.
Implement rigorous LLM evaluation frameworks and tooling
Architect LLM/RAG with prompt management, safety guardrails, and optimized inference.
Enforce data quality , lineage, and model/data cards; apply privacy-preserving techniques where needed.
Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
Prototype and benchmark new algorithms , offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.
Translate domain needs (R&D, Manufacturing, Commercial) into roadmaps; mentor teams and communicate trade-offs.

Must-Have Skills:

3-5 years in AI/ML and enterprise software.
Strong command of Agentic AI frameworks
Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel).
Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
Strong business-case skillsable to model TCO vs. NPV and present trade-offs to executives.
Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.

Good-to-Have Skills:

Experience in Biotechnology or pharma industry is a big plus
Published thought-leadership or conference talks on enterprise GenAI adoption.
Masters degree in Computer Science and or Data Science
Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

Masters degree with 12 -14+ years of experience in Computer Science, IT or related fieldOR
Bachelors degree with 14 -16 + years of experience in Computer Science, IT or related field
Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Soft Skills:

Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented, with a focus on achieving team goals.
Ability to learn quickly, be organized and detail oriented.
Strong presentation and public speaking skills.

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Principal Machine Learning Engineer