--- title: 'Staff R&D AI Engineer at webAI' canonical: 'https://feeny.ai/job/staff-r-d-ai-engineer-webai-austin-kq3t4eg8ehe9' type: 'job' last_seen: '2026-11-11' --- # Staff R&D AI Engineer at webAI - **Company:** webAI - **Location:** Austin, TX - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2025-07-25 - **Last confirmed live:** 2026-11-11 - **Apply:** https://jobs.ashbyhq.com/webAI/1d9ed4ce-ba8e-4f49-891e-ba74621ec3bc ## Job description About Us: 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. Role Overview: 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. You'll drive research initiatives, mentor technical teams, and translate breakthrough AI research into practical applications across diverse domains. Key Responsibilities: - 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 - Develop and fine-tune large language models for instruction following, reasoning, and task planning applications - Implement RLHF (Reinforcement Learning from Human Feedback) systems to improve model alignment and safety - Create multimodal training pipelines that leverage synthetic and real-world data for robust model performance - Research and prototype novel AI architectures that combine vision, language, and action learning - 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 - Present findings at conferences and publish research to advance the field Qualifications & 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 - Proven ability to work independently on complex research problems and deliver practical solutions - Strong communication skills and experience collaborating with cross-functional engineering teams Preferred Qualifications: - 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: - Truth - Emphasizing transparency and honesty in every interaction and decision. - Ownership - Taking full responsibility for one’s actions and decisions, demonstrating commitment to the success of our clients. - Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement. - Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others. Benefits: 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. - Competitive salary and performance-based incentives - Comprehensive health, dental, and vision benefits package - Including a 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 life insurance - Company-paid short and long term disability - Free parking for in-office employees 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. ## About webAI ## Company Overview - **One-liner**: webAI provides an end-to-end platform for building, deploying, and operating custom AI on local infrastructure, ensuring data sovereignty and low latency. - **Entity Type**: Private (Series A‑II, $60M total raised) - **Headquarters**: Austin, Texas, United States - **Founded**: 2019 (source: webai.com) / 2020 (source: CB Insights) - **Founders**: David Stout (CEO), Ethan Baird (Chief Research Officer), Tyler Mauer (Chief Product Officer) ## Core Business - Primary industry/industries: Enterprise AI infrastructure, sovereign AI, edge computing - Target customers: B2B – large enterprises and public‑sector organizations in healthcare, manufacturing, financial services, aviation, retail, and defense - Mission or purpose statement: “AI should be specialized, sovereign, efficient, and sustainable. It should solve real problems, not just burn more compute.” (source: [webai.com/about](https://www.webai.com/about)) ## Products & Services - **Navigator**: Build, train, and deploy custom AI models on local infrastructure with full transparency and control. (source: [webai.com](https://www.webai.com)) - **Companion**: An on‑device assistant that connects employees to private AI, tailored to industry workflows (e.g., aviation, manufacturing). (source: [webai.com](https://www.webai.com)) - **Runtime**: Orchestrates distributed AI workloads across heterogeneous hardware, scaling from a single device to entire clusters. (source: [webai.com](https://www.webai.com)) - **webFrame**: Delivers optimized inference and training with adaptive quantization (“Entropy‑Weighted Quantization”) achieving near 99.5% accuracy. (source: [webai.com](https://www.webai.com)) - **Network**: Connects every model, dataset, and device through a secure, local fabric for high‑speed collaboration without the cloud. (source: [webai.com](https://www.webai.com)) - **CLI**: Full command‑line control for developers to build, extend, and manage AI environments at scale. (source: [webai.com](https://www.webai.com)) ## Competitive Advantages - **Data sovereignty**: Full ownership of AI models and data; models run on local infrastructure, not in the cloud. - **Low latency & resilience**: Edge deployments enable real‑time inference without cloud dependency; works offline. - **Proprietary optimization**: Entropy‑Weighted Quantization compresses models while maintaining ~99.5% accuracy. - **Full‑stack platform**: Covers development (Navigator), deployment (Runtime/CLI), inference (webFrame), and collaboration (Network). ## Strategic Focus - Current priorities: Scaling custom, sovereign AI into regulated industries (healthcare, finance, defense); building the “operating system of the future” for edge intelligence; achieving 2030 vision of billions of specialized models embedded in everyday systems. (source: [webai.com/about](https://www.webai.com/about)) - Growth direction: Public sector partnerships (President of Public Sector Dr. Jason Rathje); vertical solutions for aviation, manufacturing, and retail. ## Why Work Here - **Culture**: Core beliefs include ownership, truth, tenacity, humility, and the conviction that AI must be local and accessible. - **Work model**: Flexible work environment with a strong bias toward work‑life balance; “Unlimited PTO.” - **Perks** (source: [webai.com/careers](https://www.webai.com/careers)): - Comprehensive health coverage for body and mind - Parental leave and fertility support - 401(k) with company contribution - Learning stipend for professional development - Equity options - **Engineering culture**: Developer‑first (CLI, Runtime) with focus on solving complex distributed‑systems and ML challenges; autonomy to shape the platform. ## Sources 1. [webai.com](https://www.webai.com) 2. [webai.com/about](https://www.webai.com/about) 3. [webai.com/careers](https://www.webai.com/careers) 4. [CB Insights](https://www.cbinsights.com/company/webai) 5. 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