{"id":2042131,"url":"https://alion.io/job/ultralytics-embedded-computer-vision-engineer","title":"Embedded Computer Vision Engineer","company":{"id":7376,"name":"Ultralytics","domain":"ultralytics.com","url":"https://alion.io/company/ultralytics","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Madrid, Spain"],"countries":["ES"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":50000,"max_usd":118000,"period":"year","method":"role_country_seniority_unknown","sample_n":25},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"ONNX","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"OpenVINO","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Quantization","optional":false},{"name":"TensorRT","optional":false},{"name":"Ultralytics","optional":false},{"name":"YOLO","optional":false},{"name":"C++","optional":true},{"name":"Edge AI","optional":true}],"status":"live","first_seen_at":"2026-10-07T16:47:34Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-10T22:47:12Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Ultralytics:\nAt Ultralytics, we commit to relentless innovation in the AI space and seek team members who resonate with our ambition to produce the world's best YOLO AI models. If you're obsessed with AI, eager to make an impact on the world, and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.\nJoin the team powering the future of vision AI\nHello, hola, 你好, こんにちは, नमस्ते, hallo, bonjour! Thanks for stopping by - we know your time is valuable, so here's what makes Ultralytics special.\nWho we are\nAt Ultralytics, we're on a mission to simplify AI for everyone. As the creators of the world's leading Ultralytics YOLO models, we empower millions of developers, researchers, and companies worldwide to build state-of-the-art computer vision applications with our open-source tools.\nFollowing our $30M Series A round, we're expanding rapidly across our global hubs in London, Madrid, and Shenzhen. This is an opportunity to join a fast-scaling, high-performance team that's redefining the future of vision AI - where ambition meets impact, and ideas become reality.\nWe move fast. We build boldly. We execute with purpose. And we do it together.\nAbout the role\nAs Embedded Computer Vision Engineer, you'll take YOLO models from PyTorch to production on edge hardware. You'll build and maintain export and inference integrations in the Ultralytics package, helping models run accurately and efficiently across CPU, GPU, NPU, and SoC platforms.\nYou'll own technical integrations with silicon and hardware partners, translating between model requirements and platform constraints. Working across export formats, inference runtimes, and real devices, you'll ensure partners and their customers can deploy YOLO with confidence.\nThis senior role suits an engineer with strong ML fundamentals, hands-on edge hardware experience, and the communication skills to work directly with internal teams and external partners.\nWhat you'll do\nExport & runtime integration\nBuild and maintain export and inference integrations, from model conversion to on-device support.\n\nKeep integrations working across Python, PyTorch, and vendor SDK releases.\n\nReview partner contributions and validate integrations on real hardware before release.\n\nDeployment, benchmarking & accuracy\nSet up embedded boards and development kits for YOLO deployment and testing.\n\nOptimize models for target hardware, balancing latency, memory, and accuracy.\n\nDebug accuracy loss caused by conversion and INT8 quantization.\n\nBenchmark and profile YOLO tasks and model generations, publishing results in the documentation.\n\nPartner integrations\nOwn technical relationships with hardware and silicon partners, including active AMD work and integrations with Google and Nvidia platforms.\n\nLead partner engineering syncs and define clear integration guidelines.\n\nTranslate platform constraints into model, runtime, and deployment requirements.\n\nWork with partner compiler teams to support new YOLO architectures at launch.\n\nInfrastructure, documentation & support\nDiagnose issues across models, runtimes, drivers, and devices with ML engineers and partner teams.\n\nMaintain hardware CI on self-hosted and partner-hosted devices, plus deployment Docker images.\n\nWrite integration guides and device benchmark pages.\n\nCreate developer content, live sessions, and demos for industry events.\n\nSupport developers and customers through GitHub, the community forum, and our sales team.\n\nSkills and experience\nCore requirements\nStrong foundation in machine learning or computer vision, including how YOLO models work.\n\nStrong Python skills and working experience with PyTorch and ONNX.\n\nHands-on experience with TensorRT, OpenVINO, ONNX Runtime, or a vendor NPU SDK.\n\nExperience with INT8 quantization, calibration, and debugging accuracy loss after conversion.\n\nHands-on edge device experience with NVIDIA Jetson, Raspberry Pi, or NPU development boards.\n\nExperience flashing, configuring, and debugging deployments on constrained hardware.\n\nComfortable with Linux, Docker, and Python dependency management across platforms.\n\nStrong software engineering practices, including clean code, Git pull requests, and code review.\n\nClear written English for documentation and communication with internal and external teams.\n\nSenior-level experience owning technical integrations end to end with minimal oversight.\n\nPassion for AI, computer vision, and practical, high-impact engineering.\n\nNice to have\nDirect experience working with silicon vendors or hardware partners.\n\nExperience across multiple embedded and edge ecosystems.\n\nC++ experience, including model deployment on microcontrollers.\n\nExperience running CI on self-hosted hardware runners.\n\nContributions to open-source projects or developer ecosystems.\n\nExperience collaborating across international teams.\n\nWillingness to travel to industry events.\n\nCultural fit\nAt Ultralytics, we set bold goals and execute with speed, precision, and teamwork. We're driven by hard work, ambition, and resilience - building fast, learning constantly, and delivering measurable impact.\nYou'll thrive here if you:\nTake ownership and deliver results with focus and accountability.\n\nCombine strategic thinking with hands-on execution.\n\nValue excellence, grit, and creativity in equal measure.\n\nSee collaboration as the foundation for meaningful progress.\n\nOur culture is built around our core values:\nRelentless progress: Constant evolution and improvement.\n\nStrive for excellence: Perseverance and attention to detail.\n\nActions, not words: Focus on delivering meaningful results.\n\nAct with urgency: Seize fleeting opportunities.\n\nOpen access to all: Transparent communication and collaboration.\n\nLearn more in our Ultralytics Handbook.\nCompensation and benefits\nWe reward excellence and impact - not just tenure or title.\nCompetitive salary: Reflecting your experience and contribution.\n\nEquity packages: We want our success to be yours too.\n\nOn-site collaboration: Work with passionate builders in one of our global hubs.\n\nFlexible working hours: We value results over routines.\n\nGenerous time off: 24 vacation days, your birthday off, plus local holidays.\n\nTech & tools: Work on cutting-edge AI projects that power millions of devices.\n\nGear: Brand-new Apple MacBook Air/Pro, Apple Studio Display, and AirPods Pro 3.\n\nLearning & development: Dedicated budget for personal and professional growth.\n\nHigh impact: Your work will shape the future of vision AI.\n\n Check out ultralytics.com/careers for more about our culture, values, and teams.\nWhere and how you can work\nWe believe great work happens where passion meets purpose.\nThis role is on-site in Madrid.\n\nApplicants must have legal authorization to work in the country of application.\n\nWe're an in-office team that values daily collaboration, energy, and connection. Being together helps us move faster, learn from one another, and celebrate wins as they happen.\nWhy join us\nWe're not just building models - we're building the ecosystem powering the future of vision AI. If you're ready to build, move fast, and make an impact - this is your moment.\nReady to build the ecosystem powering the future of vision AI?Apply now.\nWhat we offer:\nCutting-Edge, Next-Generation AI Computer Vision Technology: Contribute to building cutting-edge computer vision AI models based on the YOLO framework.\nImpactful Work: Shape the future of AI-powered solutions that transform industries.\nCollaborative Culture: Join a talented and passionate team that values open communication and innovation.\nUltralytics Handbook\nComprehensive guide to our company's mission, vision, values, and operational practices. This handbook is designed to provide key insights and resources for our (future) team members, collaborators, and community to align with Ultralytics' core principles.\nLink: https://handbook.ultralytics.com/\nUltralytics is an equal opportunity employer committed to building an inclusive workplace. 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