MLOps Engineer

About the Position

MLOps Engineer

Our client, a Silicon Valley-based industry leader in retail AI solutions, is now looking for an experienced MLOps Engineer to join its expanding team. The role is remote and can be based in Poland, Portugal, or the UK.

Responsibilities

• Design, build, and operate large-scale deep learning inference pipelines processing millions of images per day across multiple model services - optimized for low latency, high throughput, GPU efficiency, and compute cost.
• Plan and manage GPU fleet capacity - drive GPU utilization and cost efficiency (reservations, right-sizing, blue/green headroom).
• Own observability for inference services: metrics, tracing, dashboards, and alerting on latency, throughput, accuracy, and availability.
• Safely roll out deep learning models via staged/canary releases that protect accuracy and latency, with fast and reliable rollback.
• Detect and respond to latency regressions, accuracy degradation, and unavailability - lead incident response and root-cause analysis; uphold a 99.9% uptime SLO (on-call rotation).
• Partner with engineering teams on backend data needs - ensure data persists in usable formats for front-end, middleware, diagnostics, and model training/eval.
• Build tooling for discoverability and access to the company's datasets across geographies and data formats.

Requirements

• 5+ years building and operating production systems spanning ML serving, backend services, and infrastructure.
• Bachelor's Degree or higher in CS, EE - or equivalent practical experience.
• Excellent programming skills in Python.
• Strong experience with containerization and orchestration: Docker, Kubernetes, Helm.
• Great understanding of SQL, KeyValue stores, networking, distributed systems, operating systems, data structures, algorithms, and software engineering practices.
• Experience with streaming / event-driven pipelines using Kafka (or equivalent).
• Experience with high-availability operations management, including deployment automation and rollback strategies.
• Startup mentality, team player and willing to work 40+ hours a week.
• Advanced English skills (written and spoken).

Nice to Have

• Ray / Ray Serve (or comparable distributed compute/serving frameworks).
• MongoDB / Atlas at scale, including vector search (or similar NoSQL/KV stores).
• Observability stack: Grafana / Prometheus.
• GPU cost optimization and capacity planning.

We Offer

• Competitive salary.
• Stock options package.
• Quarterly team retreats.

About the Company

The company is the industry leader in retail AI solutions - a Silicon Valley-based startup headquartered in San Francisco, with operations in Canada, the UK, multiple EU countries, and a tech hub in Poland. Their mission is to automate and optimize brick-and-mortar retail through deep learning computer vision. Their technology has been deployed at scale with some of the world's top retailers, processing hundreds of millions of images per day across tens of thousands of stores globally.