Solutions Engineer at Ultralytics in London

Job description

• Application
• As a Solutions Engineer, you'll turn complex computer vision problems into production systems built on YOLO. You'll lead technical discovery, design architectures, build benchmarks and proof-of-concepts, and guide customers from their first conversation to deployed models.
• You'll work across Sales, Customer Success, Product, and Engineering while partnering directly with customers in manufacturing, retail, security, robotics, and beyond. This is a hands-on role for an engineer who enjoys writing Python, training and optimizing models, deploying across cloud and edge, and owning outcomes throughout the customer lifecycle.
• If you thrive on ambiguous problems, direct customer contact, and turning technical possibilities into measurable results, you'll fit right in.
• 📈 What success looks like
• 3 months: Ramped on the YOLO stack and customers, co-running discovery, and delivering your first demos and project kickoffs.
• 6 months: Owning technical discovery and POCs end to end, unblocking live deals or at-risk accounts, and earning trust from the AEs and CSMs you support.
• 9 months: Converting technical evaluations into wins or saves, shipping reusable assets, and providing actionable feedback to the wider organization.
• 12 months: Becoming the technical partner AEs and CSMs want on their biggest accounts, with POCs that convert and referenceable customer deployments.

Responsibilities

• Technical discovery and solution design
• Own technical discovery, translate customer needs into architectures, and define measurable success criteria.
• Evaluate customer data, recommend models, and design training, inference, and deployment strategies.
• Lead technical qualification and solution design alongside Account Executives and Customer Success Managers.
• Prototyping and deployment
• Build Python prototypes with YOLO, OpenCV, PyTorch, and Docker.
• Create benchmarks, integrations, and production-ready training and deployment workflows.
• Deploy solutions across Linux, macOS, Windows, cloud, and edge environments.
• Diagnose performance, data quality, inference, and hardware acceleration challenges.
• Use the Ultralytics documentation and YOLO guides to deliver reliable customer outcomes.
• Customer engagement and enablement
• Deliver technical demos, workshops, architecture reviews, and proof-of-concepts that move opportunities forward.
• Explain machine learning clearly to engineers, operators, executives, and other non-technical audiences.
• Build trusted relationships and manage technical stakeholders from evaluation through production.
• Ecosystem contribution
• Turn customer solutions into reusable examples, deployment guides, integrations, and documentation.
• Share feedback with Product and Engineering to improve the YOLO ecosystem.
• Engage developers through the Ultralytics community and GitHub organization.

Requirements

• Core requirements
• Strong Python and practical experience with YOLO, OpenCV, PyTorch, and computer vision.
• Experience training, optimizing, evaluating, and deploying machine learning models.
• Comfortable with Docker, Git, REST APIs, Linux, cloud platforms, and edge workflows.
• Experience deploying across Linux, macOS, and Windows environments.
• Proven ability to deliver technical demos, workshops, architecture reviews, and POCs.
• Strong communication skills with both technical and executive audiences.
• Independent ownership, urgency, resilience, and results in a high-performance startup environment.
• Passion for AI, open source, and helping customers achieve real outcomes.
• Kubernetes, CUDA, TensorRT, ONNX, Jetson, or other edge accelerators.
• Experience with MLOps, model monitoring, CI/CD, or observability.
• Familiarity with AWS, Azure, GCP, serverless systems, or managed inference platforms.
• Experience integrating OpenAI or Anthropic APIs into customer tools.
• Open-source contributions or experience supporting developer communities.
• Knowledge of Ultralytics YOLO workflows and production computer vision solutions.

Skills

Required

• Python
• YOLO
• OpenCV
• PyTorch
• Computer vision
• Docker
• Git
• REST APIs
• Linux
• Cloud platforms
• Edge workflows

Preferred

• Kubernetes
• CUDA
• TensorRT
• ONNX
• Jetson
• Edge accelerators
• MLOps
• Model monitoring

Benefits

• 🌟 Why this role
• Real impact: Your solutions will power vision AI in production across systems used by millions of devices.
• Demand you don't have to manufacture: YOLO is the world's most popular computer vision model, and customers already come to us looking to do more with it.
• Build at the source: Work directly on top of the YOLO ecosystem with clear lines to Product and Engineering.
• A team that ships: Join a fast-moving, high-standard team that values results over routine.
• Customer ownership: Stay involved beyond the demo and see your technical work reach production.
• We reward excellence and impact — not just tenure or title.
• Competitive compensation: Competitive compensation packages
• On-site collaboration: Work with passionate builders in one of our global hubs (London).
• Flexible working hours: We value results over routines.
• Generous time off: 24 vacation days, your birthday off, plus local holidays.
• Tech & tools: Work on cutting-edge AI projects that power millions of devices.
• Gear: Brand-new Apple MacBook Air/Pro, Apple Studio Display, and AirPods Pro 3.
• Learning & development: Dedicated budget for personal and professional growth.
• High impact: Your work will shape the future of vision AI.
• 👉 Check out Ultralytics careers and our office locations to learn more about our culture, values, and teams.