Join our team at AMGEN Capability Center Portugal, the #1 company in Best Workplaces™(201–500 employees' category) in Portugal in 2024 by the Great Place to Work Institute. With over 500talented individuals from more than 40 nationalities, our Lisbon center thrives at the intersection of innovation, excellence, and inspiration. This is your opportunity to explore the future of healthcare through technology and digital innovation, supporting our mission To Serve Patients.

What you will do

• Collaborate with data scientists to develop, train, and evaluate machine learning models
• Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
• Leverage cloud platforms (AWS, Databricks) for ML model development, training, and deployment
• Develop solutions using DevSecOps framework that are secure, scalable, reliable, and aligned with enterprise architecture standards
• Evaluate model performance using appropriate metrics and optimize models for accuracy and efficiency
• Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
• Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
• Identify and resolve technical challenges effectively
• Provide ongoing support and maintenance for applications, ensuring that they operate smoothly and efficiently
• Analyze customer feedback and support data to identify pain points and opportunities for improvement
• Evaluate and recommend technologies and tools that best fit the solution requirements

What we expect of you

• Strong foundations in machine learning algorithms and techniques
• Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in model monitoring, including model observability and explainability
• Proficiency in Python (or R) and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
• Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
• Good understanding of cloud platforms (e.g., AWS, Databricks) and containerization technologies (e.g., Docker, Kubernetes)
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)
• Experience with data processing tools like Hadoop, Spark, or similar
• Knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, Semantic Kernel)
• Ability to analyze client requirements and translate them into solutions
• Excellent critical-thinking and problem-solving skills
• Strong communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated awareness of presentation skills

Must-Have Skills

• Machine learning algorithms and techniques
• MLOps practices and tools (MLflow, Kubeflow, Airflow)
• Model monitoring, observability and explainability
• Python (or R)
• ML libraries (TensorFlow, PyTorch, Scikit-learn)
• Big data technologies (Spark, Hadoop)
• Performance tuning in query and data processing
• Cloud platforms (AWS, Databricks)
• Containerization (Docker, Kubernetes)
• Monitoring and logging tools (Prometheus, Grafana, Splunk)
• Data processing tools (Hadoop, Spark)
• GenAI tooling (vector databases, RAG pipelines, prompt-engineering DSLs, agent frameworks like LangChain, Semantic Kernel)
• DevSecOps framework
• Agile methodologies

What you can expect of us

• Comprehensive benefits in healthcare, finance, and well-being
• Hybrid work model with time split between Lisbon office and remote work
• Access to certifications, trainings, mentorship, and career mobility
• Work that accelerates scientific breakthroughs and helps patients worldwide
• Modern tech stack: cloud-first, automation-focused, AI-powered
• Global scale with agile mindset

Compensation

201–500