webAI
Staff R&D AI Engineer
Austin, TX · Staff+
Sponsorship not specifiedDetected 362 days ago
PythonAlgorithmsAWSGCPAzureCloud PlatformsMachine LearningDeep LearningTensorFlowPyTorchNLPComputer VisionLLMsMLOpsRoboticsControlsResearchCommunication
About the role
- As a Staff R&D AI Engineer, you will lead the development of cutting-edge AI systems that bridge computer vision, natural language understanding, and action learning.
- You'll architect and implement Vision-Language-Action (VLA) models, advance reinforcement learning applications, and push the boundaries of multimodal AI integration.
- This role combines deep expertise in both computer vision and large language models with hands-on experience in reinforcement learning to create intelligent systems that can understand, reason about, and interact with complex environments.
Responsibilities
- Develop and fine-tune large language models for instruction following, reasoning, and task planning applications
- Create multimodal training pipelines that leverage synthetic and real-world data for robust model performance
- Collaborate with engineering teams to integrate AI models into applications and validate performance across domains
- Optimize model inference performance for real-time applications across edge and cloud deployments
- Lead technical initiatives, mentor junior AI engineers, and establish best practices for AI model development
- Stay current with latest research in VLA models, multimodal AI, and robotics to drive innovation roadmap
Requirements
- Proven ability to work independently on complex research problems and deliver practical solutions
Nice to have
- Experience with RLHF implementation and human feedback integration for model alignment
- Experience with real-world system deployment and sim-to-real transfer techniques
- 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
Skills
- 7+ 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
- Strong communication skills and experience collaborating with cross-functional engineering teams
Compensation
- Competitive salary
Benefits
- Comprehensive health, dental, and vision benefits package
- $200/month Health & Wellness stipend
- Continuing Education support
- $500/year Function Health subscription (U.S.-based employees only)
- Flexible Time Off (FTO)
- Parental leave for eligible employees
- Supplemental life insurance
- We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline.
- Design and develop Vision-Language-Action (VLA) models that integrate visual perception, natural language understanding, and action prediction
- Architect and implement reinforcement learning systems for sequential decision-making, including policy learning and skill acquisition
- Build and optimize computer vision pipelines for perception tasks, including object detection, segmentation, tracking, and scene understanding
- Implement RLHF (Reinforcement Learning from Human Feedback) systems to improve model alignment and safety
Company info
- 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.
This listing is sourced directly from webAI's careers page and normalized into a canonical job model.