R&D Engineer

Ultralytics

R&D Engineer designing and developing neural network architectures for YOLO at Ultralytics. Contributing to the future of AI-powered solutions through innovative research and development.

Posted 6/29/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building neural network architectures, particularly for YOLO models, with a strong focus on efficiency techniques such as quantization and pruning. Proven ability to translate research into production-ready models while maintaining high standards of accuracy and performance.

Highest-signal resume keywords

Neural Network Architecture DesignExpert-Level PythonDeep Proficiency in PyTorchQuantization and Pruning TechniquesResearch Paper Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Computer VisionDeep LearningModel Building from ScratchConvolutionsAttention MechanismsNormalization TechniquesOptimization FundamentalsLoss DesignAblation StudiesArchitecture Experiments

Soft Skills

High OwnershipAdaptabilityProblem Solving

Industry Keywords

YOLO ModelsDetectionSegmentationPose EstimationVision SystemsOpen-Source ModelsR&D CollaborationEfficiency Research

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

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.
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.
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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Competitive salary: Reflecting your experience and contribution.
Equity packages: We want our success to be yours too.
On-site collaboration: Work with passionate builders in one of our global hubs.
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.