Sr Machine Learning Engineer

Amgen; Portugal; Presencial; EUR 60 000 - 100 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Best Workplaces recognition

Lisbon office

Resumo da oferta

AMGEN Capability Center Portugal in Lisbon is hiring a Senior Machine Learning Engineer to design end-to-end ML platforms and scalable AI services. You will lead the development of core ML pipelines and secure APIs, collaborating with DevOps, Security and Product teams.

The role requires expertise in ML algorithms, GenAI tooling, and modern MLOps, with a hands-on approach to ship production-grade models and applications at enterprise scale.

Qualificações

• 3-5 years in AI/ML and enterprise software.
• Proven track record selecting and integrating AI SaaS/PaaS offerings.
• Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks.

Responsabilidades

• Engineer end-to-end ML pipelines using Kubeflow, SageMaker Pipelines, OpenAI SDK or equivalent MLOps stacks.
• Harden research code into production-grade micro-services and expose secure REST, gRPC or event-driven APIs.
• Build and maintain full-stack AI applications by integrating model services with lightweight UI components or workflow engines.
• Instrument observability with real-time metrics, distributed tracing, drift/bias detection and user-behavior analytics.
• Embed security and Responsible-AI controls in partnership with Security, Privacy and Compliance teams.

Conhecimentos

AI/ML expertise

Python

Java

MLOps

GenAI tooling

Formação académica

Master's degree in Computer Science

Ferramentas

Kubeflow

SageMaker Pipelines

OpenAI SDK

Docker

Kubernetes

LangChain

Semantic Kernel

Descrição da oferta de emprego

Career CategoryInformation SystemsJob DescriptionJoin our team at AMGEN Capability Center Portugal , consistently recognized among the top companies in the Best Workplaces(TM) ranking by Great Place to Work(R) in Portugal. In 2026, we were once again distinguished as one of the top Best Workplaces in the country (category 201-500 employees), reinforcing our commitment to an exceptional employee experience and workplace culture.We are a team of over 500 talented individuals, spanning more than 30 functions and areas of expertise, and representing over 40 nationalities. Together, we bring diverse perspectives and professional backgrounds to help shape the future of healthcare through innovation and technology.This is your opportunity to explore a world of possibilities across areas such as Data & Analytics, Digital, Technology & Innovation, Cybersecurity, R&D Operations, Global Distribution, Finance, Regulatory Affairs, General & Administrative, Human Resources, and many more.Located in the heart of Lisbon, our AMGEN office fosters a culture of innovation, excellence, and purpose. Come thrive with us at AMGEN, supporting our mission To Serve Patients.What we do at AMGEN matters in people's lives.We are seeking a Sr Machine Learning Engineer -Amgen's 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.

Roles & Responsibilities

• Engineer end-to-end ML pipelines -data ingestion, feature engineering, training, hyper-parameter optimization, 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.
• Optimize performance and cost at scale -selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantization/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-behavior 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 evangelize 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.

Must-Have Skills

• 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-with the judgment to choose, tune and operationalize the right method for a given business problem.
• 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; containerization (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.

Good-to-Have Skills

• 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