Staff R&D AI Engineer
Quick Summary
Design and develop Vision-Language-Action (VLA) models that integrate visual perception, natural language understanding,
We are establishing the first distributed Al infrastructure dedicated to personalized Al. The evolving needs of a data-driven society are demanding scalability and flexibility. We believe that the future of Al is distributed and enables real-time data processing at the edge, closer to where data is generated. We are building a future where a company's data and IP remains private and it's possible to bring large models directly to consumer hardware without removing information from the model.
Responsibilities
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Design and develop Vision-Language-Action (VLA) models that integrate visual perception, natural language understanding, and action prediction
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Architect and implement reinforcement learning systems for sequential decision-making, including policy learning and skill acquisition
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Build and optimize computer vision pipelines for perception tasks, including object detection, segmentation, tracking, and scene understanding
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Develop and fine-tune large language models for instruction following, reasoning, and task planning applications
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Implement RLHF (Reinforcement Learning from Human Feedback) systems to improve model alignment and safety
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Create multimodal training pipelines that leverage synthetic and real-world data for robust model performance
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Research and prototype novel AI architectures that combine vision, language, and action learning
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Collaborate with engineering teams to integrate AI models into applications and validate performance across domains
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Optimize model inference performance for real-time applications across edge and cloud deployments
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Lead technical initiatives, mentor junior AI engineers, and establish best practices for AI model development
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Stay current with latest research in VLA models, multimodal AI, and robotics to drive innovation roadmap
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Present findings at conferences and publish research to advance the field
We strive to provide competitive benefits to all employees. The benefits listed in this posting generally apply to U.S.-based employees. For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.
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Competitive salary
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Comprehensive health, dental, and vision benefits package
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401(k) match
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Equity options
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$200/month Health & Wellness stipend
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Continuing Education support
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$500/year Function Health subscription
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Free parking for in-office employees
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Flexible Time Off (FTO)
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Parental leave for eligible employees
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Supplemental life insurance
webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.
Requirements
~2 min read7+ years of experience in AI/ML engineering with 4+ years focusing on deep learning and neural network development
Strong understanding of reinforcement learning algorithms and their applications (PPO, SAC, TD3, etc.)
Strong expertise in both computer vision and natural language processing with hands-on model development experience
Proficiency in PyTorch and/or TensorFlow with experience training and deploying large-scale models
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 including model versioning, monitoring, and deployment pipelines
Proven ability to work independently on complex research problems and deliver practical solutions
Strong communication skills and experience collaborating with cross-functional engineering teams
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.)
Open-source contributions to major AI/ML frameworks or robotics projects
Startup experience with ability to rapidly prototype and iterate on AI solutions
Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies
Background in safety-critical AI systems or AI alignment research
We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following:
Location & Eligibility
Listing Details
- Posted
- July 25, 2025
- First seen
- September 25, 2026
- Last seen
- September 28, 2026
Posting Health
- Days active
- 2
- Repost count
- 0
- Trust Level
- 21%
- Scored at
- September 28, 2026
Signal breakdown
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