Tech Lead Manager (Synthetic Data)

Location: London, United Kingdom; hybrid working model with in-person collaboration in the office and remote work.

Company

hirify.global is building an AI platform for autonomous driving that learns directly from real-world experience and supports scalable deployment across vehicles and geographies.

What you will do

• Lead the Synthetic Data team within Simulation and set the technical direction for generative world-model capabilities.
• Design the synthetic-data pipeline and controllability engine, including rig transfer, pose transfer, conditioning, evaluation, and reproducible lineage.
• Connect large-scale GPU generation and evaluation with downstream driving-model training.
• Improve inference efficiency, sampling, KV caching, valid-generation rates, and self-serve synthetic-data workflows.
• Collaborate with world-model researchers, infrastructure engineers, driving-model owners, and evaluation and safety teams.
• Hire, structure, manage, coach, and develop a high-performing team of ML engineers and applied scientists.

Requirements

• 5+ years of experience in ML engineering or applied research, with experience training and shipping neural networks.
• 4+ years of people management experience, including direct reports and cross-functional project ownership.
• Deep knowledge of generative modeling, including diffusion, flow matching, autoregressive models, or VAEs, applied to video or high-dimensional temporal data.
• Experience with video, generative, or world models, such as video generation, novel-view synthesis, neural rendering, or controllable generation.
• Working knowledge of cameras and 3D geometry, including multi-camera rigs, camera parameters, warps, and reprojection.
• Strong Python and PyTorch fundamentals, plus experience operating multi-GPU generation or training workflows and large video artifacts.

Nice to have

• Experience taking generated or simulated data into downstream model training and measuring impact through mix ratios, ablations, and failure analysis.
• Experience with video generation, camera transfer, distillation, or other state-of-the-art generative-modeling techniques.

Culture & Benefits

• Hybrid working with core hours and opportunities to work hands-on in vehicle workshops and labs.
• Relocation support and visa sponsorship where applicable.
• Learning and development budgets for training, conferences, and professional growth.
• Market-benchmarked salaries, equity, health and dental insurance, enhanced parental leave, retirement or pension benefits, therapy access, and wellbeing partnerships.
• An evolving environment with significant ownership, ambiguity, and influence over how the organization operates.

Hiring process

• Initial recruiter call lasting approximately 30 minutes.
• Competency interviews covering programming, PyTorch debugging, and the hiring manager interview.
• Deep-dive systems and domain-specific interviews, followed by a final mission and values interview.