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Apptronik is a Series B human-centered robotics company developing AI-powered humanoid robots (Apollo) to support humanity across manufacturing, logistics, healthcare, and beyond. The company operates at the cutting edge of applied AI, solving critical challenges in safety, commercialization, and mass production.
You will lead the "brain" and "nervous system" of Apptronik's humanoid robots as Vice President of Embodied AI. This role owns the company's AI strategy and leads a world-class, multi-disciplinary organization of 45+ engineers and researchers across real-time controls, whole-body reinforcement learning, dexterous manipulation, vision-language model (VLA) post-training, and agentic autonomy.
Key responsibilities include:
**AI Strategy & Technical Vision**: Define and own the embodied AI vision and roadmap aligned with product strategy and long-term autonomy goals. Drive technical decision-making around model architectures and the role of internal models versus strategic partners and third-party foundation/VLA models. Establish architectural principles for composing learned and classical components into safe, reliable robotic systems. Partner with the CEO, CTO, and executive team to translate complex AI capabilities into commercial milestones.
**Controls Stack Unification**: Architect a unified controls strategy bridging high-level semantic reasoning (VLAs and agentic planning), mid-level policy execution (RL), and low-level deterministic real-time control. Define clean interfaces, arbitration, and fallback behavior so capability gains compound rather than conflict. Ensure the unified stack meets latency, stability, and safety requirements for dynamic humanoid platforms operating around people.
**Model Development & Autonomy**: Lead development of models and policies powering the robot, including state estimation, real-time control, whole-body RL locomotion, dexterous manipulation, VLA post-training, and agentic task planning. Establish best practices for fine-tuning, distillation, compression, safety constraints, and continuous learning. Define evaluation criteria and benchmarks tying model performance to real-world robotic outcomes. Guide adaptation of strategic partner and third-party models into production.
**Data Collection & Learning Strategy**: Own the end-to-end data strategy for training state-of-the-art embodied AI. Define what data to collect, from which sources, at what scale, and to what quality bar. Drive data collection programs across teleoperation, real-world robot fleets, and synthetic data/simulation. Set dataset requirements, curation standards, and quality metrics. Direct simulation environment design for training, evaluation, and sim-to-real transfer.
**Customer-Centric Deployment**: Ensure controllers are reliable, safe, and deliver tangible ROI for customers. Own the definition of model readiness for deployment—the performance, safety, and robustness criteria models must meet before reaching customer sites. Use field telemetry and deployment feedback to close the loop between real-world behavior, data collection priorities, and model improvement.
**Thought Leadership & Recruiting**: Act as an ambassador within the global AI and robotics communities. Publicize key findings aligned with IP strategy and build strategic research and industry relationships. Attract, hire, and retain top-tier engineering and research talent.
**Team & Organizational Leadership**: Directly manage and scale a multi-disciplinary organization across real-time controls, whole-body RL, dexterous hand control, VLA post-training, and autonomy frameworks. Collaborate with software, infrastructure, and hardware organizations to ensure the AI stack is well-supported from training through on-robot deployment. Set engineering and research standards, review practices, and career development paths. Foster a culture of technical excellence, experimentation, accountability, and cross-functional collaboration.
**Requirements**
*Required Experience:*
- 10+ years in robotics, AI, or machine learning, with 5+ years in senior leadership (VP/Director) managing large, multi-disciplinary technical organizations (40+ engineers/researchers)
- Deep technical fluency across the modern robotics stack, including trade-offs between classical control theory, reinforcement learning, and modern foundation models (VLAs, world action models, LLMs)
- Demonstrated capability of taking complex, AI-driven hardware or robotics systems out of R&D and successfully deploying them to external customers in the real world—balancing "perfect" research with "good enough to ship"
- Experience defining and scaling the data strategy behind large-scale action models: teleoperation, real-world collection, auto-labeling, and sim-to-real transfer
- Respected presence in the AI/robotics research community (e.g., publications at ICRA, IROS, CoRL, NeurIPS, CVPR) with a network that supports strategic hiring and partnerships
- Exceptional communication: able to distill complex technical constraints into clear strategic decisions for the executive team while diving deep into architecture discussions with staff engineers
*Strongly Preferred:*
- Direct experience with humanoid or legged robotics, dexterous manipulation, or dynamic whole-body control
- Experience integrating and co-optimizing with strategic partners or third-party foundation and VLA models
- Experience navigating the safety and compliance challenges of deploying autonomous robots in human-centric environments
- Advanced degree in Robotics, Computer Science, ML, or a related field
