R&D Engineer
Company shown to members 🔒 · Remote · US, Spain only
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First recorded by Psst: 12 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- 5+ years required
- Where you can live
- US, Spain only
- Skills and tools
- python, documentation
- Job type
- Full-time
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Job details
- Where you can work
- United States, Spain
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- 5+ years required
- Employer publication date
- 29 June 2026
- First recorded by Psst
- 12 October 2026
- Last checked at the source
- 10 November 2026
About the job
About the company
At the company [link for members] we commit to relentless innovation in the AI space and seek team members [link for members] who resonate with our ambition to produce the world's best YOLO AI models [link for members] 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 the company [link for members] we're on a mission to simplify AI for everyone. As the creators of the world's leading open-source YOLO models [link for members] and the popular the company GitHub repository [link for members] we empower millions of developers, researchers, and companies worldwide to build state-of-the-art computer vision applications.
Following our $30M Series A round [link for members] 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 [link for members] 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 company ecosystem [link for members] and contribute to the technical foundations documented in our docs [link for members] and guides [link for members]
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.
EXPERIMENTATION & OPTIMIZATION
- Run rigorous ablation studies and large-scale architecture experiments across standard benchmarks.
- 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.
COLLABORATION & OWNERSHIP
- Partner with R&D and engineering teams to turn research ideas into production-ready open-source models.
- 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.
NICE TO HAVE
- Published research at venues such as CVPR, ICCV, ECCV, NeurIPS, or ICLR.
- 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 company Python package [link for members] documentation [link for members] or community forum [link for members]
- History of taking original research from prototype to models others actually use.
🌟 CULTURAL FIT
At the company, 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.
You'll thrive here if you
- Take ownership and deliver results with focus and accountability.
- Combine deep technical thinking with hands-on execution.
- Value excellence, grit, and creativity in equal measure.
- See collaboration as the foundation for meaningful progress.
Our culture is built around our core values
- Relentless progress: Constant evolution and improvement.
- 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.
Learn more in the company Handbook [link for members] and Mission & Values [link for members]
💰 COMPENSATION AND BENEFITS
We reward excellence and impact — not just tenure or title.
- Competitive salary: Reflecting your experience and contribution.
- 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 the company [link for members] for more about our culture, values, and teams.
What we offer
Cutting-Edge, Next-Generation AI Computer Vision Technology: Contribute to building cutting-edge computer vision AI models based on the YOLO framework.
Impactful Work: Shape the future of AI-powered solutions that transform industries.
Collaborative Culture: Join a talented and passionate team that values open communication and innovation.
The company Handbook
Comprehensive 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 the company' core principles.
Link: [link for members]
The company is an equal opportunity employer committed to building an inclusive workplace. We believe that everyone should be able to bring their whole selves to work, and we do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or any other legally protected status.
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