Senior ML Infrastructure Engineer (DevOps)

About the role

We are seeking a Senior ML Infrastructure Engineer who loves running production systems at scale. You will work closely with applied scientists, taking ownership of the end‑to‑end infrastructure that powers real‑time inference for millions of customers.

Key responsibilities

• Maintain healthy real‑time inference services through alerting, live debugging, incident resolution, rollbacks and post‑mortems as part of a 24x7 on‑call rotation.
• Design, build and improve AWS infrastructure using IaC, CI/CD pipelines, Kubernetes, Docker, autoscaling, monitoring and cost‑control mechanisms.
• Manage the GPU fleet: NVIDIA driver and CUDA upgrades, node provisioning, debugging and capacity planning.
• Automate user access, including SSH credentials, service accounts and developer environments for the science team.
• Run real‑time production data pipelines, stream ingestion into an online feature store and serve features to low‑latency endpoints.
• Orchestrate batch jobs with Airflow or Databricks Workflows.
• Partner with applied scientists to productionise prototypes and keep them operational.
• Write and review production‑grade Python code, including validation of AI‑generated code.

Required profile

• Proven 24x7 on‑call experience with high‑load online services, including live incident debugging.
• Strong Linux systems expertise with hands‑on Kubernetes, Docker and infrastructure‑as‑code.
• Solid Python, Git and CI/CD experience.
• Experience with workflow orchestration tools such as Airflow or Databricks Workflows.
• Proficiency in DevOps practices and CI/CD pipelines.
• Familiarity with generative AI in the software development lifecycle.
• English proficiency at B2 level or higher.

Required skills

• Python
• Git
• CI/CD
• AWS
• Kubernetes
• Docker
• Infrastructure as Code (e.g., Terraform, CloudFormation)
• Apache Airflow
• Databricks Workflows
• Linux
• NVIDIA drivers & CUDA

What we offer

• Innovative projects with global impact.
• Flexible work environment – office or home.
• Opportunities to work abroad up to two months per year.
• Relocation options across 55+ countries.
• Leadership development, certifications (GCP, Azure, AWS) and unlimited learning resources.
• Medical & family care package, referral bonuses, six trust days, psychology session coverage, fitness discounts.