VLA/WAM Research Engineer (Robotics)

Location: San Francisco, United States; benefits and robotics facilities are also listed for Zurich, Switzerland.

Company

hirify.global builds the intelligence layer for humanoid robots and develops foundation models for real-world robotic deployment.

What you will do

• Design VLA and World-Action Model architectures combining vision, language, robot state, actions, and temporal context.
• Develop large-scale pretraining across diverse robot embodiments, teleoperation, egocentric human data, and simulated experience.
• Improve data mixtures, training objectives, optimization strategies, and distributed training workflows.
• Develop predictive world and action models for representation learning, future-state prediction, planning, and policy improvement.
• Adapt pretrained models to new tasks, environments, embodiments, and capabilities, including post-training and reinforcement learning.
• Design continual-learning methods and rigorous evaluations using autonomous rollouts, failures, interventions, simulation, and real robots.

Requirements

• Strong Python and PyTorch skills with hands-on experience developing and training modern deep-learning models.
• Research or engineering experience in VLA/VLM architectures, multimodal foundation models, world models, large-scale pretraining, robot learning, or RL/post-training.
• Experience owning substantial model-development or training experiments, including architecture choices, objectives, optimization, and evaluation.
• Strong understanding of modern deep-learning architectures, representation learning, and the relationship between data, objectives, and model performance.
• Ability to design rigorous experiments, diagnose training failures, and use empirical results to guide research decisions.
• Familiarity with large-scale datasets, model-training workflows, and generalization across tasks, environments, or embodiments.
• Ability to evaluate recent research and translate promising ideas into working models and experiments.
• Comfort working across architecture, training, and adaptation, with particular expertise in at least one of these areas.

Nice to have

• Experience with VLA, VLM, diffusion, flow-matching, video/world models, or other multimodal generative architectures.
• Experience with distributed training, multi-node GPU systems, large-scale data mixtures, and foundation-model optimization.
• Experience with reinforcement learning, offline RL, reward/value learning, specialist distillation, or continual learning.
• Experience with predictive world models, video generation, latent dynamics, or self-supervised representation learning.
• Experience with multi-embodiment robot learning, action representations, or adapting policies across robot platforms.
• Experience with teleoperation, egocentric video, simulation, autonomous rollouts, or large-scale embodied datasets.
• Experience evaluating learned policies on real robots, especially humanoids or dexterous manipulation systems.

Culture & Benefits

• Full-time role with competitive compensation, an enhanced pension plan, enhanced holiday and paid-leave benefits, and relocation and permit sponsorship.
• Central Zurich office with robotics testing facilities and infrastructure.
• San Francisco benefits include 401(k) contributions, health, dental and vision coverage, open PTO, and paid company holidays.
• Energetic, collaborative culture with a bias for action and regular community events.