Staff R&D AI Engineer

Skills

About the Role

You will lead the development of multimodal AI systems combining computer vision, language understanding, and action learning. You will architect Vision-Language-Action models, reinforcement learning systems, and large-scale training pipelines. You will optimize models for real-time edge and cloud deployment, integrate them into applications, mentor junior engineers, lead technical initiatives, and present and publish research findings.

Requirements

• 7+ years of AI/ML engineering experience, including 4+ years focused on deep learning and neural network development
• Understand reinforcement learning algorithms and applications, including PPO, SAC, and TD3
• Demonstrate expertise in computer vision and natural language processing
• Use PyTorch and/or TensorFlow to train and deploy large-scale models
• Understand transformer architectures, attention mechanisms, and large language model fine-tuning
• Have hands-on experience with object detection, semantic segmentation, and visual tracking
• Program in Python and use distributed training and model optimization
• Understand sequential decision-making and control systems
• Use MLOps practices, including model versioning, monitoring, and deployment pipelines
• Work independently on complex research problems and deliver practical solutions
• Communicate effectively and collaborate with cross-functional engineering teams

Responsibilities

• Design and develop Vision-Language-Action models that integrate visual perception, natural language understanding, and action prediction
• Architect and implement reinforcement learning systems for sequential decision-making, policy learning, and skill acquisition
• Build and optimize computer vision pipelines for object detection, segmentation, tracking, and scene understanding
• Develop and fine-tune large language models for instruction following, reasoning, and task planning
• Implement RLHF systems to improve model alignment and safety
• Create multimodal training pipelines using synthetic and real-world data
• Research and prototype AI architectures combining vision, language, and action learning
• Collaborate with engineering teams to integrate AI models into applications and validate performance
• Optimize model inference for real-time edge and cloud deployments
• Lead technical initiatives, mentor junior AI engineers, and establish model-development best practices
• Track research in VLA models, multimodal AI, and robotics
• Present findings at conferences and publish research

Benefits

• Comprehensive health, dental, and vision benefits package
• 401(k) match
• Equity options
• $200/month Health & Wellness stipend
• Continuing Education support
• $500/year Function Health subscription
• Free parking for in-office employees
• Flexible Time Off
• Parental leave for eligible employees
• Supplemental life insurance