Staff R&D AI Engineer

The role

You will lead the development of AI systems bridging computer vision, natural language understanding, and action learning. You will architect VLA models, advance reinforcement learning, and translate research into practical applications.

What you will do

• Design and develop Vision-Language-Action (VLA) models
• Architect and implement reinforcement learning systems
• Build and optimize computer vision pipelines
• Develop and fine-tune large language models
• Implement RLHF systems
• Create multimodal training pipelines
• Research and prototype novel AI architectures
• Collaborate with engineering teams to integrate AI models
• Optimize model inference performance
• Lead technical initiatives and mentor junior AI engineers

Required qualifications

• 7+ years of experience in AI/ML engineering
• 4+ years focusing on deep learning and neural network development
• Strong understanding of reinforcement learning algorithms (PPO, SAC, TD3, etc.)
• Strong expertise in both computer vision and natural language processing
• Proficiency in PyTorch and/or TensorFlow
• Experience with transformer architectures, attention mechanisms, and large language model fine-tuning
• Hands-on experience with computer vision tasks including object detection, semantic segmentation, and visual tracking
• Strong programming skills in Python with experience in distributed training and model optimization
• Understanding of sequential decision-making and control systems fundamentals
• Experience with MLOps practices
• Proven ability to work independently on complex research problems
• Strong communication skills and experience collaborating with cross-functional engineering teams

Nice to have

• PhD in Computer Science, Robotics, AI/ML, or related field with focus on multimodal learning or robotics
• Direct experience developing or working with Vision-Language-Action (VLA) models or similar multimodal architectures
• Experience with RLHF implementation and human feedback integration for model alignment
• Background in imitation learning, inverse reinforcement learning, or learning from demonstrations
• Experience with real-world system deployment and sim-to-real transfer techniques
• Knowledge of 3D computer vision, spatial reasoning, or multi-modal perception systems
• Experience with distributed training frameworks (DeepSpeed, FairScale, Horovod) and large-scale model training
• Familiarity with edge AI deployment and model optimization techniques (quantization, pruning, distillation)
• Experience with embodied AI research or projects involving agent-environment interaction
• Published research in top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CoRL, etc.)

Benefits

• Competitive salary and performance-based incentives
• Comprehensive health, dental, and vision benefits package
• High-deductible HSA option with company contribution
• 401k match (US-based only)
• Flexible PTO Policy
• Parental leave for eligible employees
• Continuing education support
• Basic, company-paid life insurance
• Supplemental insurance
• Company-paid short term and long term disability
• Free parking for in-office employees

About the company

webai is establishing the first distributed AI infrastructure dedicated to personalized AI. They believe the future of AI is distributed and enables real-time data processing at the edge.