U

Ultralytics

Develops real-time computer vision AI models

Founding Engineer

Full-Time
No salary listed
Senior, Expert
New York, NY, USA
HybridHybrid role based in the New York office.
Software EngineeringFull-Stack Engineering

About the job

Requirements
  • Senior-to-principal/distinguished-level industry delivery, with sustained ownership of feature areas and tech-lead-level accountability.
  • Shipped machine learning/artificial intelligence and computer vision work, with practical Python and PyTorch proficiency beyond coursework or research.
  • Full-stack capability spanning user interfaces, application programming interfaces, databases, cloud infrastructure, deployment, and production operations.
  • Current AI-assisted development experience, sound review judgment, and a preference for mainstream, well-documented tools.
  • Strong asynchronous communication, work breakdown, and deadline delivery within structured teams; no degree is required, but industry experience is essential.
Responsibilities
  • Own a feature area from requirements and architecture through implementation, testing, deployment, and iteration.
  • Ship machine learning/computer vision capabilities alongside full-stack interfaces, backend services, and infrastructure, using the company's documentation and guides.
  • Use Copilot or Codex routinely, validating generated code for correctness, security, and maintainability.
  • Break ambiguous work into milestones, align dependencies across locations, and communicate decisions and blockers asynchronously.
  • Balance customer needs, technical trade-offs, and commercial deadlines with Product and Engineering.
  • Lead design and code reviews, unblock engineers, and set standards for testing, observability, and production reliability.
  • Strengthen the open-source ecosystem through maintainable contributions, technical documentation, and engineering knowledge-sharing.
Desired Qualifications
  • Production experience with TypeScript, React, and Python API frameworks such as FastAPI.
  • Experience with PostgreSQL, Docker, continuous integration/continuous delivery, infrastructure as code, and cloud platforms.
  • Hands-on model serving, GPU optimization, inference monitoring, or edge deployment experience.
  • Contributions to Ultralytics or other open-source projects and engagement with the developer community.
  • Early engineering experience building products and establishing technical practices across international teams.

About the company

U

Ultralytics

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Website

Ultralytics builds computer vision AI tools to help people create, train, and deploy models. Its main products are Ultralytics HUB, a no-code platform with drag-and-drop data handling, cloud training, team collaboration, and an inference API, and Ultralytics YOLO, a family of fast real-time detection, segmentation, classification, and tracking architectures for edge and cloud deployment. The company differentiates itself with a strong open-source base paired with an enterprise licensing model, plus paid HUB plans and managed data labeling services. Its goal is to make AI easy to use for individuals and organizations by simplifying the journey from data to deployed AI at scale.

Company Size

51-200

Company Stage

Series A

Total Funding

$30M

Headquarters

London, United Kingdom

Founded

2014

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Simplify Jobs

Simplify's Take

What believers are saying

  • Ambarella partnered with Ultralytics on September 15, 2026 for CVflow edge deployment.
  • YOLO26 launched January 2026 with sub-5ms Intel inference and faster CPU performance.
  • Ultralytics reported 140k GitHub stars, 330 million pip downloads, and 3.6 billion usages.

What critics are saying

  • YOLO trademark status shows a suspension letter on June 8, 2026, threatening branding control.
  • Open-source code remains commoditizable; Intel, Ambarella, and DEEPX can capture deployment economics.
  • Enterprise revenue depends on platform adoption, and hyperscaler alternatives can outspend Ultralytics on integrations.

What makes Ultralytics unique

  • Glenn Jocher’s YOLO lineage still anchors Ultralytics’ brand and developer mindshare in 2026.
  • YOLO27, announced September 13, 2026, spans 28 models across seven vision tasks.
  • Ultralytics Platform unifies annotation, training, deployment, and monitoring inside one workflow.

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Benefits

  • Flexible Work Hours
  • Paid Vacation
  • Paid Holidays
  • Hybrid Work Options
  • Company Equity
  • Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

9%

1 year growth

53%

2 year growth

46%
GlobeNewswire
Sep 15th, 2026
Ambarella and Ultralytics collaborate to bring Ultralytics YOLO models to cvflow-powered edge devices.

Ambarella and Ultralytics collaborate to bring Ultralytics YOLO models to cvflow-powered edge devices. The partnership is designed to give developers and product teams a more efficient path from vision model development to deployment on low-power edge AI silicon. September 15, 2026 09:00 ET | Source: Ambarella SANTA CLARA, Calif. and LONDON, Sept. 15, 2026 (GLOBE NEWSWIRE) - Ambarella, Inc. (NASDAQ: AMBA), an edge AI semiconductor company, and Ultralytics, a vision AI company known for the open-source Ultralytics YOLO model family, today announced a collaboration to support the deployment of Ultralytics YOLO models on Ambarella CVflow(R)-powered edge devices. The collaboration brings together Ultralytics' real-time computer vision models and Ambarella's low-power AI processing technology. The two teams are working to give developers a familiar starting point on silicon built for the power and thermal limitations under which edge products operate. When detection, segmentation, and tracking run locally on the device, systems can respond with lower latency, place less demand on network bandwidth, and reduce their dependence on cloud processing. For products that operate in the physical world, those characteristics shape how quickly a machine responds to what it sees, and how dependably it responds when connectivity is limited. The integration is designed to help developers and product teams build and deploy vision applications more efficiently across areas such as smart cameras, robotics, automotive, and industrial systems. "By bringing Ultralytics YOLO to Ambarella's CVflow platform, we're making it easier for developers and product teams to build efficient, real-time vision applications directly at the edge," said Glenn Jocher, Founder and CEO of Ultralytics. "This collaboration combines Ultralytics' accessible computer vision models with Ambarella's low-power AI processing, helping move vision AI from development to deployment more efficiently." On the Ambarella side, the work centers on the Cooper(TM) Developer Platform and the Ambarella Developer Zone ("DevZone"), which the company launched at CES 2026. The DevZone brings optimized models, agentic blueprints, developer kits, documentation, and technical resources into a single accessible environment. A common CVflow architecture and a shared software environment serve Ambarella's entire edge AI SoC portfolio, so perception software and development workflows can carry forward as a product line scales up in performance or moves to a lower cost point. "The edge AI markets we serve are evolving quickly, and our partner ecosystem needs a platform that meets developers in the frameworks and model families they already use," said Fermi Wang, President and CEO of Ambarella. "Ultralytics YOLO is among the most widely adopted model families in computer vision, and supporting it on our CVflow platform broadens the set of teams that can build on Ambarella silicon." Ultralytics YOLO models support object detection, instance segmentation, image classification, pose estimation, and oriented bounding box detection within a single model family, with a range of model sizes that let teams balance accuracy against the compute and memory budget a given product can carry. About Ambarella With an installed base of more than 50 million AI SoC units, Ambarella's products are utilized in a wide variety of physical edge AI applications, spanning edge endpoint and edge infrastructure use cases including physical security, vehicle safety, telematics, autonomy, portable video, aerial drones, and other emerging robotic applications. Building on this footprint, Ambarella offers a full-stack edge AI platform, from highly optimized silicon and programmable software to AI agentic frameworks that coordinate perception, decision-making, and control across devices. Ambarella's low-power systems-on-chip (SoCs) integrate proprietary and highly efficient perception and deep learning neural network AI accelerators, enabling electronic systems to become more productive with partial or complete levels of machine autonomy. For more information, please visit www.ambarella.com. About Ultralytics Ultralytics is the leading force in vision AI, best known for its Ultralytics YOLO (You Only Look Once) models and Ultralytics Platform, the ultimate end-to-end computer vision platform where users can annotate, train, and deploy vision AI solutions in one place. With over 140k GitHub stars, 330 million PiP downloads, and 3.6 billion model usages, Ultralytics YOLO has become the most widely recognized object detection model globally. Ultralytics empowers users with easy-to-use, cutting-edge AI technology. Our mission is to simplify and democratize the use of AI, making it accessible and impactful across industries ranging from manufacturing to healthcare and more. Media Contact Jonathan Miller [email protected]

Associated Press
Jul 14th, 2026
Ultralytics YOLO26 brings sub-5ms inference to Intel CPUs and NPUs for edge AI deployment

Ultralytics has partnered with Intel to optimise its YOLO computer vision models for Intel processors. The collaboration enables deployment across CPU, GPU, and NPU platforms using Intel's OpenVINO Toolkit, achieving sub-5-millisecond inference on Intel hardware. The integration allows developers to deploy YOLO models on existing Intel-powered infrastructure without requiring discrete GPUs. Applications span manufacturing quality inspection, logistics tracking, retail inventory monitoring, healthcare imaging, robotics, and smart cities. Developers can train and export applications using Ultralytics' existing platform with a single command. The partnership brings real-time vision AI to edge devices including industrial PCs, laptops, and factory-floor equipment. Ultralytics' YOLO models have accumulated over 135,000 GitHub stars and 3.3 billion model usages globally.

PR Newswire
May 14th, 2026
DEEPX and Ultralytics partner to set physical AI standard for YOLO's 16.6M monthly downloads

DEEPX, a Seoul-based AI semiconductor company, has partnered with Ultralytics, creator of the widely deployed YOLO computer vision architecture, to establish a global standard for physical AI applications. The alliance integrates DEEPX's ultra-low-power neural processing units directly into the Ultralytics ecosystem, which sees over 16.6 million monthly downloads. Developers can now deploy computer vision models to DEEPX hardware using a single command, format=deepx, within the Ultralytics Python package. The partnership includes automated model quantization pipelines and continuous integration to ensure compatibility with future updates. DEEPX's mass-produced DX-M1 NPU will serve as the foundational hardware for applications in robotics, industrial machinery and smart vehicles. The companies count Hyundai Motor Group, Baidu and over 50 customers globally amongst their clients.

Tech in Asia
Apr 13th, 2026
Korean chip startup DeepX debuts AI module in Japan.

Korean chip startup DeepX debuts AI module in Japan. Fabless chip company DeepX showed its mass-produced DX-M1 module at Japan DX Week 2026 in Tokyo, as it moves to win customers in Japan's embedded IoT and robotics markets. DeepX said it plans to unveil the DX-M2 in H2 to widen its push into chips for robots and industrial equipment. The company also said partners demos with DX-M1, and that distributors visiting its booth highly rated the module's power-performance ratio, while DeepX cited demand in Japan for high-performance, low-power edge AI systems. Food for thought. Implications, context, and why it matters. DeepX arrives in Japan with proven global traction * DeepX enters Japan after landing 27 commercial purchase orders in eight countries within seven months of starting mass production of the first-generation DX-M1 AI chip 1. * Ahead of mass production, DeepX ran proof-of-concept trials with about 350 companies worldwide, which helped fill the sales pipeline early 2. * DeepX also set up distribution through Avnet, DigiKey, and WPG, a Taiwan-based semiconductor distribution group. Analysts call this an uncommon step for an emerging fabless semiconductor company, which designs chips but outsources manufacturing, at this stage 1. The next-generation chip aims to move more AI workloads off the cloud * The upcoming DX-M2 targets large language models with up to 100 billion parameters while using less than 5 watts of power 3. * DeepX expects the chip to shift heavier AI tasks from data centers to edge devices, with a forecast of cutting data center traffic by more than 80% 3. * This move may pressure the pay-per-use AI service model used by cloud providers, push more value toward hardware makers, and support autonomous robots that run without network connectivity 3. * DeepX is forming an "Open-Source Physical AI Alliance" with Ultralytics, known for AI computer vision software, and Baidu PaddlePaddle, the AI development platform of Chinese tech company Baidu, to widen the developer ecosystem for edge deployment 3. Stay updated on the go with our mobile app. Get latest insights with smoother, more personalized experience through TIA mobile app. How would you feel if you could no longer use Tech in Asia? Share, tag us, and land on our Wall of!

Yahoo Finance
Mar 18th, 2026
Ultralytics launches end-to-end vision AI platform with 2.5B daily inferences

Ultralytics, the company behind the YOLO object detection models, has launched Ultralytics Platform, an end-to-end vision AI development system. The platform integrates annotation, cloud training with 22 GPU options, and deployment across 43 regions in a single environment. With 125,000 GitHub stars and 225 million package downloads, Ultralytics' YOLO models power 2.5 billion daily inferences across manufacturing, logistics, healthcare and autonomous vehicles. The platform addresses fragmentation in computer vision workflows by connecting previously separate tools for dataset creation, training and deployment. Since launch, developers have uploaded over 50 million images and created more than 150 million annotations. The platform features SAM-powered smart annotation, real-time experiment tracking and built-in production monitoring.