Sr Machine Learning Engineer Job at Amgen (Hyderabad)

Sr Machine Learning Engineer

Amgen

Location:
India , Hyderabad

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We are seeking a Sr Machine Learning Engineer—Amgen’s most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms. Sitting at the intersection of engineering excellence and data-science enablement, you will design the core services, infrastructure and governance controls that allow hundreds of practitioners to prototype, deploy and monitor models—classical ML, deep learning and LLMs—securely and cost-effectively. Acting as a “player-coach,” you will establish platform strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI developer experience.

Job Responsibility:

Engineer end-to-end ML pipelines—data ingestion, feature engineering, training, hyper-parameter optimisation, evaluation, registration and automated promotion—using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks
Harden research code into production-grade micro-services, packaging models in Docker/Kubernetes and exposing secure REST, gRPC or event-driven APIs for consumption by downstream applications
Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency
Optimise performance and cost at scale—selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantisation/pruning, and tuning GPU/CPU auto-scaling policies to meet strict SLA targets
Instrument comprehensive observability—real-time metrics, distributed tracing, drift & bias detection and user-behaviour analytics—enabling rapid diagnosis and continuous improvement of live models and applications
Embed security and responsible-AI controls (data encryption, access policies, lineage tracking, explainability and bias monitoring) in partnership with Security, Privacy and Compliance teams
Contribute reusable platform components—feature stores, model registries, experiment-tracking libraries—and evangelise best practices that raise engineering velocity across squads
Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness
Partner with data scientists to prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs

Requirements:

3-5 years in AI/ML and enterprise software
Comprehensive command of machine-learning algorithms—regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques
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
Master’s degree with 6-11 + years of experience in Computer Science, IT or related field OR Bachelor’s degree with 8-13 + years of experience in Computer Science, IT or related field
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

Nice to have:

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 and or Data Science
Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery
Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus

Additional Information:

Job Posted:
January 09, 2026

Work Type:

On-site work

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