3 days ago
Lisbon, PortugalMid Level / Senior
Responsibilities
- Define component boundaries, acceptance criteria, non-functional requirements, support expectations, and estimates with product and architecture partners.
- Design and implement maintainable Python, SQL, data, model, retrieval, agent-tool, workflow, and API components with testing, error handling, configuration, and documentation.
- Apply exploratory data analysis, feature engineering, supervised and unsupervised methods, validation, calibration, explainability, and error analysis where relevant.
- Build GenAI, NLP, RAG, and bounded-agent components using embeddings, hybrid search, reranking, provenance, citations, permissions, approvals, and recoverable failure handling.
- Engineer batch and event-driven data, document, feature, embedding, label, and evaluation pipelines with validation, lineage, provenance, access control, and consistency checks.
- Define evaluation for model quality, retrieval, grounding, citations, task success, tool correctness, safety, latency, cost, and user impact.
- Release and support components using cloud services, containers, CI/CD, versioning, monitoring, rollback, incident response, and runbooks.
- Apply security, privacy, Responsible AI, validation, auditability, human oversight, and applicable GxP controls, while guiding Associate engineers on familiar work.
Requirements
- A Master’s degree and 4–6 years of Computer Science, IT, or related experience, or a Bachelor’s degree and 6–8 years, or a Diploma and 9–10 years.
- Demonstrated ownership of at least one production software, data, ML, GenAI, or automation component.
- Strong hands-on proficiency in Python and SQL with sound software-engineering and testing practices.
- Strong capability in at least one of classical ML, GenAI/RAG/agents, or MLOps/platform engineering, with working knowledge of adjacent areas.
- Knowledge of production software and AI/ML system design, statistics, modeling, experimentation, data and cloud-scale systems, AI evaluation, MLOps/LLMOps, and responsible regulated delivery.
- Preferred experience includes PyTorch, TensorFlow, Hugging Face, scikit-learn, XGBoost, PyMC, computer vision, NLP, GNNs, causal inference, uncertainty estimation, GenAI orchestration, cloud platforms, MLOps tools, agent workflows, and regulated or healthcare environments.
- Ability to solve problems independently, communicate assumptions and trade-offs clearly, collaborate across technical and business functions, follow through reliably, and guide junior engineers.
Tech Stack
Apache AirflowApache SparkAWSDatabricksGitHub ActionsKubernetesMLflowPythonPyTorchscikit-learnSQLTensorFlowXGBoost
Categories
About Amgen
Amgen is a public biotechnology company that discovers, develops, manufactures, and sells biologic and biosimilar therapeutics for patients with serious diseases. Its portfolio and pipeline span oncology, cardiovascular disease, osteoporosis, inflammation, and rare diseases, marketed globally through direct sales and partnerships. Founded in 1980 and headquartered in Thousand Oaks, California (NASDAQ: AMGN), Amgen is a component of the Dow Jones Industrial Average and completed the acquisition of Horizon Therapeutics in 2023.