Applied Scientist/Machine Learning Engineer (Generative Simulation)

Location: Hybrid full-time role based in the London or Sunnyvale office, with time split between office and home working.

Salary: USD 311,000–512,000 per year for Sunnyvale, depending on experience and performance.

Company

hirify.global develops autonomous driving technology and generative AI systems for mobility and safety.

What you will do

• Develop efficient generative world models using diffusion, transformer, or hybrid architectures for real-time roll-outs and controllable scene editing.
• Architect interactive world models that support reinforcement learning, planning, and safety evaluation loops.
• Optimize end-to-end inference performance through latent compression, context pruning, and related techniques.
• Define metrics for long-horizon coherence, physics fidelity, and planner integration; run ablations and scaling studies.
• Integrate simulation models into closed-loop training and evaluation, and measure the sim-to-real gap against on-road driving-model results.
• Mentor junior researchers, shape technical roadmaps, publish at leading venues, and represent hirify.global in the research community.

Requirements

• 4+ years of machine learning research or engineering experience focused on generative video or world models.
• Deep knowledge of diffusion and latent-video models, with experience improving sampling efficiency or model throughput.
• Experience working with high-dimensional temporal or spatiotemporal data, such as video or multisensor fusion.
• Strong Python and PyTorch engineering skills, including research-grade production tools.
• Strong publication record or contributions to open-source machine learning tooling.
• Ability to collaborate in a fast-paced, innovative, interdisciplinary environment.

Nice to have

• Experience in autonomous vehicles, robotics, simulation, or embodied AI.
• Experience with synthetic-to-real transfer.

Culture & Benefits

• Work on autonomous driving technology with real-world mobility, safety, and AI applications.
• Access to large driving datasets, advanced infrastructure, and research expertise.
• High-trust, high-autonomy environment focused on creativity, experimentation, and deep technical thinking.
• Opportunities to publish, share research, and shape generative AI for autonomy.
• Core working hours with flexibility to determine a suitable schedule with the team.

Hiring process

• The CV is used to pre-fill as much of the application form as possible.