Machine learning engineer for computer vision

Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. We're looking for a Senior ML Systems Engineer to join Encord's in-house ML team.

• Design, build and operate model-serving and inference infrastructure for transformer-based vision and multimodal models
• Own the serving architecture behind our ML features, justifying trade-offs in latency, throughput, reliability and GPU cost
• Optimise models and pipelines for production through batching, KV caching, GPU utilisation and orchestration
• Integrate models into Encord's product and annotation workflows together with Product Engineering
• Build reusable abstractions that work across models, data types, customers and changing task templates
• Set up monitoring and observability, and own performance and reliability once features are live
• Take prototypes from your research-focused teammates and turn them into shipped features
• Contribute to platform design decisions, take part in design reviews and help us hire
• Work with Python, PyTorch, CUDA, Kubernetes and GCP/AWS

• An owner. You take ambiguous product needs, make the architecture calls and carry the work all the way into production.
• A systems thinker. You design for scale and reuse, and you know when a simple, solid baseline beats a clever solution.
• A great collaborator. You enjoy working across research, product and engineering, and you make it easier for everyone to ship.
• A bridge between research and production. You speak both languages, help researchers get their work shipped, and feed production lessons back into how models are built.
• 5+ years of software engineering experience, including meaningful time building and operating ML systems or model-backed products in production at scale
• Strong software engineering and system design fundamentals
• Hands-on experience deploying modern deep learning models in production, with a strong understanding of model serving, inference optimisation, GPU utilisation and performance trade-offs.
• Experience designing and operating scalable, distributed production systems, ideally involving GPU workloads, high-throughput data processing or low-latency inference.
• The ability to reason through an ML system end to end, from data and model choices to offline and online evaluation, deployment, monitoring and retraining
• A track record of personally owning complex systems from design through to production
• Будет плюсом: computer vision or multimodal deployment experience (not required), model-serving frameworks, or experience with video, 3D or other complex data types

• Competitive salary and meaningful equity in a high-growth startup
• Strong in-person culture — most of the team works from our London office 4+ days/week
• 25 days annual leave + UK public holidays
• Annual learning & development budget
• Travel for customer visits, events, and conferences across the UK and Europe
• Daily company lunches
• Monthly socials & bi-annual team offsites