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Principal
Principal Machine Learning Engineer
Confirmed live in the last 24 hours
Amgen
India - Hyderabad
On-site
Posted April 18, 2026
Job Description
Career Category
Information SystemsJob Description
The AI/ML Lead will head Amgen’s AI/ML practice within the Innovation Lab, driving the development, validation, and deployment of machine learning and GenAI solutions across R&D, Manufacturing, and Commercial domains.
This role requires strong technical depth, leadership skills, and a deep understanding of responsible AI frameworks within regulated environments.
Key Responsibilities
- Lead AI/ML strategy and implementation across multiple PoDs in the Innovation Lab.
- Translate Amgen’s business objectives into data-driven AI/ML initiatives.
- Define architecture, standards, and best practices for model design, training, and validation.
- Oversee MLOps and CI/CD integration to enable scalable model deployment.
- Guide the team on data preparation, feature engineering, and experimentation.
- Review and approve model validation reports, metrics, and explainability artifacts.
- Ensure compliance with Responsible AI, GxP, and privacy frameworks.
- Collaborate with SMEs and Data Governance leads to align models with business and ethical objectives.
- Mentor engineers, fostering innovation and technical excellence.
Required Qualifications
- 10–15 years of experience in data science or machine learning engineering.
- Proven leadership in AI/ML project delivery and technical governance.
- Expertise in Python, TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
- Experience with MLOps, MLflow, Databricks, and AWS SageMaker.
- Strong grounding in model lifecycle management and validation documentation.
- Excellent analytical, communication, and cross-functional collaboration skills.
Preferred Skills
- Experience with GenAI / LLM architectures (LangChain, OpenAI APIs, Hugging Face).
- Prior exposure to pharma, biotech, or life sciences R&D.
- Certification in Machine Learning / Data Science / AWS AI Specialist.
- Familiarity with data privacy regulations (HIPAA, GDPR) and ethical AI standards.
machine learning
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