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Machine Learning Engineer, AI Studio

Amgen Inc.
Posted a month ago

LOCATION

India · Onsite

EXPERIENCE

5 - 9 Years

TYPE

FullTime

SKILLS REQUIRED

Machine LearningSQLPythonMLOpsRetrieval Augmented GenerationEmbeddings

Job description

Overview

Machine Learning Engineer (AI Studio) with independent ownership of defined production ML/AI components for enterprise AI products and automation solutions.

What you'll do

  • Define component boundaries, intended use, acceptance criteria, and support expectations with product and architecture partners.
  • Design and implement maintainable Python, SQL, API, data, model, retrieval, agent-tool, and workflow components with testing, error handling, and documentation.
  • Apply statistical and ML techniques such as EDA, feature engineering, supervised/unsupervised methods, cross-validation, and error analysis.
  • Build GenAI/NLP/RAG/bounded agent components including structured output, embeddings, hybrid search, reranking, and citations.
  • Engineer batch or event-driven pipelines for data, documents, features, embeddings, labels, and evaluation with validation and lineage.
  • Define evaluation measures for quality, uncertainty, retrieval grounding, safety, latency, cost, and user impact.
  • Release and support components using cloud services, containers, CI/CD, monitoring, rollback, and incident response.

What you'll need

  • Bachelor’s or Master’s degree.
  • 5 to 9 years of Computer Science, IT, or related field experience.
  • Production software/AI-ML system design skills using Python and SQL, APIs, background jobs, event flows, testing, performance, observability, and source control.
  • Statistics, modeling, and experimentation skills including EDA, feature engineering, cross-validation, leakage prevention, calibration, and uncertainty work.
  • GenAI/RAG/agent skills including prompt/context management, structured output, chunking, embeddings, hybrid retrieval, reranking, citations, and access-aware retrieval.
  • Batch/event-driven pipeline experience using data stores and cloud-scale systems.
  • Experience with AI evaluation and MLOps/LLMOps practices such as versioning, CI/CD, release gates, monitoring, incidents, and runbooks.

Details

  • Career level: GCF 4 – Senior Associate.
  • Career track: Individual Contributor.
  • Organization: Applied AI | AI Studio.

Read the full description and apply on the company’s own careers page.

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Machine Learning Engineer, AI Studio