
Principal Data Scientist
- Hyderabad, Telangana
- Permanent
- Full-time
- Define and evangelise the multi-year AI-platform vision, architecture blueprints and reference implementations that align with Amgen’s digital-transformation and cloud-modernization objectives.
- Design and evolve foundational platform components—feature stores, model-registry, experiment-tracking, vector databases, real-time inference gateways and evaluation harnesses—using cloud-agnostic, micro-service principles.
- Implement robust MLOps pipelines (CI/CD for models, automated testing, canary releases, rollback) and enforce reproducibility from data ingestion to model serving.
- Embed responsible-AI and security-by-design controls—data-privacy, lineage tracking, bias monitoring, audit logging—through policy-as-code and automated guardrails.
- Serve as the ultimate technical advisor to product squads: codify best practices, review architecture/PRs, troubleshoot performance bottlenecks and guide optimisation of cloud resources.
- Partner with Procurement and Finance to develop TCO models, negotiate enterprise contracts for cloud/AI infrastructure, and continuously optimise spend.
- Drive platform adoption via self-service tools, documentation, SDKs and internal workshops; measure success through developer NPS, time-to-deploy and model uptime SLAs.
- Establish observability frameworks—metrics, distributed tracing, drift detection—to ensure models remain performant, reliable and compliant in production.
- Track emerging technologies (serverless GPUs, AI accelerators, confidential compute, policy frameworks like EU AI Act) and proactively integrate innovations that keep Amgen at the forefront of enterprise AI.
- 5-7 years in AI/ML, data platforms or enterprise software, including 3+ years leading senior ICs or managers.
- 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, Semantic Kernel).
- Proficiency in Python and Java; containerisation (Docker/K8s); cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
- Strong business-case skills—able to model TCO vs. NPV and present trade-offs to executives.
- Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.
- Experience in Biotechnology or pharma industry is a big plus
- Published thought-leadership or conference talks on enterprise GenAI adoption.
- Master’s degree in Computer Science, Data Science or MBA with AI focus.
- Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.
- Master’s degree with 10-14 + years of experience in Computer Science, IT or related field
- Bachelor’s degree with 12-17 + 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.
- 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.