R&D Engineer

About Ultralytics: At Ultralytics https://ultralytics.com/, we commit to relentless innovation in the AI space and seek team members https://www.ultralytics.com/about who resonate with our ambition to produce the world's best YOLO AI models https://ultralytics.com/yolo. 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. ⚡ WHO WE ARE At Ultralytics https://www.ultralytics.com/, we're on a mission to simplify AI for everyone. As the creators of the world's leading open-source YOLO models https://docs.ultralytics.com/models/ and the popular Ultralytics GitHub repository https://github.com/ultralytics, we empower millions of developers, researchers, and companies worldwide to build state-of-the-art computer vision applications. Following our $30M Series A round https://www.ultralytics.com/news/ultralytics-raises-30m-series-a, 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. We move fast. We build boldly. We execute with purpose. And we do it together. 💼 ABOUT THE ROLE As an R&D Engineer focused on neural network architectures for YOLO, you'll design and develop the neural network architectures at the core of how YOLO https://docs.ultralytics.com/models/ is built. Your work will directly shape the open-source models used by millions of developers across detection, segmentation, pose, and emerging vision tasks. You'll operate at the intersection of research and production, turning ideas from papers into performant architectures, rigorous experiments, and production-ready model designs. Working closely with our cross-disciplinary R&D team, you'll help define future releases across the Ultralytics ecosystem https://www.ultralytics.com/ and contribute to the technical foundations documented in our docs https://docs.ultralytics.com/ and guides https://docs.ultralytics.com/guides/. This role is ideal for a hands-on researcher who thrives on first-principles thinking, rapid experimentation, and high ownership. You bring deep architectural intuition, strong PyTorch skills, and the drive to build original models that advance the state of the art. 🚀 WHAT YOU'LL DO RESEARCH & ARCHITECTURE DESIGN - Research, design, and build novel neural network architectures for next-generation YOLO models.

• Develop core components including backbones, necks, heads, attention modules, and efficient building blocks.
• Read, reproduce, and extend cutting-edge papers into working model architectures from scratch.

• Improve accuracy, latency, and scaling through distillation, pruning, and quantization-aware design.
• Build training recipes and evaluation pipelines for detection, segmentation, pose, and new vision tasks.

• Contribute to foundational model initiatives that support future YOLO and broader vision systems.
• Take ownership of assigned R&D tasks beyond architecture work and solve problems efficiently and correctly. 🧠 SKILLS AND EXPERIENCE CORE REQUIREMENTS - 5+ years of hands-on experience in computer vision and deep learning with architecture design expertise.
• Proven success building models from the ground up, not just fine-tuning pretrained checkpoints.
• Expert-level Python and deep proficiency in PyTorch, including custom layers, modules, and training loops.
• Strong command of convolutions, attention, normalization, optimization, and loss design fundamentals.
• Ability to read a research paper and implement it faithfully and efficiently from scratch.
• Experience with efficiency research such as quantization, pruning, distillation, or neural architecture search.
• Strong portfolio of research contributions through papers, preprints, open-source code, or original model work.
• High ownership, adaptability, and comfort operating in a fast-moving research environment.

• Experience with distributed training, mixed precision, CUDA profiling, or model deployment constraints.
• Active open-source presence with architecture-focused repositories and meaningful community adoption.
• Familiarity with the Ultralytics Python package https://github.com/ultralytics/ultralytics, documentation https://docs.ultralytics.com/, or community forum https://community.ultralytics.com/.
• History of taking original research from prototype to models others actually use. 🌟 CULTURAL FIT At Ultralytics, we set bold goals and execute with speed, precision, and teamwork.

• Combine deep technical thinking with hands-on execution.
• Value excellence, grit, and creativity in equal measure.
• See collaboration as the foundation for meaningful progress.

• Strive for excellence: Perseverance and attention to detail.
• Actions, not words: Focus on delivering meaningful results.
• Act with urgency: Seize fleeting opportunities.
• Open access to all: Transparent communication and collaboration.

• Competitive

Salary

• Equity packages: We want our success to be yours too.
• Global collaboration: Work with passionate builders across our global team.
• 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. 🌎 WHERE AND HOW YOU CAN WORK This is a remote role. 👉 Check out ultralytics.com/careers https://www.ultralytics.com/careers for more about our culture, values, and teams.

What we Offer

• Showcase a portfolio of fully‑implemented research papers, preferably with public GitHub links that demonstrate end‑to‑end training pipelines.
• Highlight concrete examples of architecture design where you built a model from scratch rather than fine‑tuning existing weights.
• Prepare to discuss your process for reproducing results, including how you handle hyper‑parameter search and ablation studies.
• Emphasize any contributions to open‑source vision libraries; Ultralytics values community‑driven work.
• During interviews, be ready to write a small PyTorch module on the whiteboard to prove deep‑level API knowledge.
• Ask about the team’s experiment tracking stack and how they handle large‑scale benchmarking; it shows proactive thinking.
• Negotiate by referencing the equity component and remote‑work stipend as standard parts of Ultralytics' compensation philosophy.