Machine Learning Engineer à Grande-Bretagne

Runware is building a high-performance, full-stack AI media-creation platform — empowering developers and companies to generate any type of media instantly. As we scale fast and integrate increasingly complex models, we need stronger visibility, analytics, and monitoring across the whole platform stack.

Your main goal is to give Runware full visibility over:

• End-to-end inference performance
• Integration usage and model activity
• Errors, delays, bottlenecks, regressions
• Internal and client-facing analytics dashboards
• Health and performance of production pipelines

You will provide the data insights that allow engineering, ML, backend, DevOps, and leadership to make informed decisions — and to continuously improve performance and reliability.

• Build and maintain E2E inference time tracking (global and per-model).
• Monitor how implementation changes impact total request latency.
• Detect regressions introduced by suboptimal code paths.
• Provide automated alerts & historical trends.

• Build dashboards for internal use (engineering, product, leadership).
• Provide client-facing usage dashboards (requests, errors, success rate, performance).
• Support clients who need visibility to debug their integrations.
• Track model-level usage, API endpoints usage, adoption metrics, etc.

• Implement metrics, logs, and traces that help the entire platform scale smoothly.
• Work closely with DevOps & backend teams to improve system observability.
• Provide insights that guide infra decisions (GPU allocation, autoscaling, caching, batching, etc.).

• Select and maintain tooling (e.g., Prometheus/Grafana, Datadog, OpenTelemetry, ELK, BigQuery, etc.).
• Ensure data pipelines are reliable, accessible, and always up-to-date.
• Build simple, easy-to-read dashboards for both technical and non-technical teams.

• Strong experience with data analytics, observability, or monitoring
• Hands-on with metrics/logging/tracing frameworks (Prometheus, Grafana, Datadog, New Relic, etc.)
• Good understanding of backend systems and distributed architectures
• Ability to turn raw metrics into actionable insights
• Experience building dashboards for internal and external stakeholders
• Familiarity with AI model monitoring (latency, throughput, error codes, GPU utilization)

• Experience with AI/ML infrastructure, inference pipelines, GPUs
• Understanding of Python APIs, FastAPI, or Node environments
• Experience working with high-throughput real-time systems
• Startup or scale-up experience

• A problem-solver mindset
• Proactivity — you like digging into the data and flagging problems before anyone else sees them
• Ability to work with ML, backend, DevOps, and product teams
• Comfort with autonomous ownership

We're a remote-first collective, meeting in person twice a year to plan, brainstorm, celebrate wins, and enjoy some face-to-face time. We have core hours for cooperative working and calls, but outside of that your calendar is yours. Work the hours that let you perform at your peak while also building a healthy life.

Our release cycles are fast and intense, but they're followed by real downtime. After big pushes we expect the team to unplug, recharge, and come back ready & stronger than ever for the next leap.

• Generous paid time off - vacation, sick days, public holidays
• Meaningful stock options - share in the upside you create
• Remote-first setup - work from home anywhere we can employ you
• Flexible hours - own your schedule outside core collaboration blocks
• Family leave - paid maternity, paternity, and caregiver time
• Company retreats - twice-yearly gatherings in inspiring locations

Please note: We are unable to offer visa sponsorship in the UK at this time. Candidates must have existing right to work in the UK.