Robotics VLA/WAM Deployment Engineer (Relocation Sponsorship)

Flexion; San Francisco (CA); Presencial; USD 140.000 - 210.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Pension plan

Holiday & leave perks

Relocation sponsorship

Central Zürich office

Leading robotics team

Energetic culture

Descripción de la vacante

Flexion in San Francisco is seeking a VLA/WAM Integration and Deployment specialist to turn research into reliable humanoid capabilities. You will deploy learned policies across humanoid platforms, optimize inference, collect data, and evaluate real-world performance.

You will work across model training, deployment, data pipelines, and robotics hardware, partnering with engineers to improve end-to-end system reliability in dynamic environments.

Formación

• Strong Python and PyTorch skills and experience with modern deep-learning systems.
• Experience deploying learning-based models in robotics, autonomous systems, or another real-time embodied setting.
• Familiarity with VLA, VLM, diffusion, flow-matching, video/world-model, or related multimodal architectures.
• Strong systems intuition around inference latency, model serving, data pipelines, logging, and debugging complex ML systems.
• Experience designing rigorous evaluation and diagnosing failures in learned systems.
• Comfort working directly with robots, sensors, data collection, and imperfect real-world hardware.
• Ability to work across model training, deployment, data, infrastructure, and integration rather than within a narrowly defined research area.

Responsabilidades

• VLA/WAM Deployment: Deploy and validate learned policies across humanoid platforms and real-world tasks.
• Fast Inference: Optimize model serving, latency, action generation, asynchronous execution, and closed-loop control for real-time robot operation.
• Agentic Integration: Connect VLA/WAM policies with higher-level agents for task decomposition, policy selection, structured conditioning, verification, recovery, and replanning.
• In-Situ Data Collection: Develop improved workflows for teleoperation, interventions, autonomous rollouts, failures, recoveries, and targeted post-training data collection.
• Evaluation & Testing: Develop reproducible real-robot evaluations, regression suites, failure analysis, and principled comparisons between model versions.
• Deployment-to-Training Loop: Turn real-world successes and failures into datasets and experiments that improve subsequent pre-training and post-training.

Conocimientos

Python

PyTorch

Robotics deployment

Real-time systems

Evaluation design

Robotic hardware

cross-disciplinary collaboration

Herramientas

TensorRT

Torch.compile

Quantization

Model compression

Descripción del empleo

Flexion in San Francisco is seeking a VLA/WAM Integration and Deployment specialist to turn research into reliable humanoid capabilities. You will deploy learned policies across humanoid platforms, optimize inference, collect data, and evaluate real-world performance.

You will work across model training, deployment, data pipelines, and robotics hardware, partnering with engineers to improve end-to-end system reliability in dynamic environments.