Senior Machine Learning Engineer
Posted Updated
Summary
Senior ML engineer on Swiss Post's internal Data & AI Engineering platform team in Lisbon, building reusable Terraform modules, ML lifecycle tooling (tracking, registry, pipelines), and GenAI components (LLM routing, agent lifecycle, guardrails) on cloud infrastructure. Python, Kubernetes/EKS, cloud platforms; hybrid with one mandatory office day per week.
You'll join the internal Data & AI Engineering platform team, responsible for the tooling and components that enable data and AI use cases across the company. The team builds on top of existing cloud infrastructure - owning the data and AI layer: reusable modules, lifecycle tooling, agentic components, and the internal developer experience for teams building on the platform.
You'll contribute to design, own implementation, and work directly with internal teams that consume what you build.
What you can do
− Building and maintaining reusable platform components: Terraform modules, deployment blueprints, and abstractions that internal ML and GenAI teams depend on
− ML lifecycle tooling: experiment tracking, model registry, deployment pipelines, monitoring
− GenAI-specific components: LLM access and routing, agent lifecycle and versioning, tool integrations, guardrails, evaluations
− CI/CD for ML and GenAI workloads
− Supporting internal teams in adopting platform components - documentation, examples, hands-on guidance where needed
What you bring
− You have more than 5 years of proven experience working with AI.
− Solid engineering fundamentals - maintainable code, clear system design thinking, ability to own deliverables end-to-end
− Cloud platform experience (AWS, GCP, Azure, or Databricks).
− Infrastructure-as-code experience; Terraform exposure is a plus
− Python proficiency
− Experience building and maintaining ML workflows end-to-end - training pipelines, experiment tracking, model registry, deployment, and monitoring.
− Deploying and maintaining AI Solutions in kubernetes, preferrably in EKS.
− Familiarity with relevant tooling (e.g. MLflow, SageMaker Pipelines, Kubeflow, or similar).
− Hands-on experience with LLMs or GenAI tooling in a technical context - working with model APIs, building or operating agentic systems, or contributing to GenAI infrastructure (evaluation, observability, guardrails, etc.)
− Knowledge and Experience with GPU Utilization Optimization (e.g. vLLM) is a plus
Education
− University/technical college degree in computer science or comparable.
Language Skills
− English oral and written
− Optional: German oral (and written)− Willingness to travel
− Hybrid Model: One day a week @office (mandatory)Just by joining us you will get benefits like:
You'll contribute to design, own implementation, and work directly with internal teams that consume what you build.
What you can do
− Building and maintaining reusable platform components: Terraform modules, deployment blueprints, and abstractions that internal ML and GenAI teams depend on
− ML lifecycle tooling: experiment tracking, model registry, deployment pipelines, monitoring
− GenAI-specific components: LLM access and routing, agent lifecycle and versioning, tool integrations, guardrails, evaluations
− CI/CD for ML and GenAI workloads
− Supporting internal teams in adopting platform components - documentation, examples, hands-on guidance where needed
What you bring
− You have more than 5 years of proven experience working with AI.
− Solid engineering fundamentals - maintainable code, clear system design thinking, ability to own deliverables end-to-end
− Cloud platform experience (AWS, GCP, Azure, or Databricks).
− Infrastructure-as-code experience; Terraform exposure is a plus
− Python proficiency
− Experience building and maintaining ML workflows end-to-end - training pipelines, experiment tracking, model registry, deployment, and monitoring.
− Deploying and maintaining AI Solutions in kubernetes, preferrably in EKS.
− Familiarity with relevant tooling (e.g. MLflow, SageMaker Pipelines, Kubeflow, or similar).
− Hands-on experience with LLMs or GenAI tooling in a technical context - working with model APIs, building or operating agentic systems, or contributing to GenAI infrastructure (evaluation, observability, guardrails, etc.)
− Knowledge and Experience with GPU Utilization Optimization (e.g. vLLM) is a plus
Education
− University/technical college degree in computer science or comparable.
Language Skills
− English oral and written
− Optional: German oral (and written)− Willingness to travel
− Hybrid Model: One day a week @office (mandatory)Just by joining us you will get benefits like:
- Open minded company where every employee has to contribute to the development of the company - ideas are welcome as well as independent thinking to
- 25 annual days of vacations
- Flexible working hours
- Annual allowance for Benefits (Training, Gym, Public Transportation, Technologies, etc...)
- An amazing onboarding week at Switzerland
- iPhone
- Second Screen to work at home (Flat or a Curved one)
- First month Tech Allowance to buy your headset or, if you already have one, whatever you need to work comfortably
- Health insurance for you and your family
- Life insurance
- Office Perks (coffee, fruit, stand up desks. etc...)
- So much more...