Lead Machine Learning Engineer (Autonomous Driving)

Location: London, United Kingdom. Hybrid working with in-person collaboration in offices and workshops, combined with focused remote work.

Company

hirify.global develops an AI platform for autonomous driving, combining machine learning, robotics, simulation, and vehicle systems to support scalable, hardware-agnostic autonomy.

What you will do

• Lead and develop a London-based team of Senior Machine Learning Engineers while remaining deeply involved in technical direction.
• Set the architecture for robust, scalable offline scene-understanding and measurement models.
• Translate ambiguous business goals into sprint, quarterly, annual, and multi-year technical roadmaps.
• Review designs and code, raise engineering quality standards, and ensure models are reliable for customer-facing deliverables.
• Align roadmaps across on-vehicle modelling, foundation models, Evaluation, Simulation, and Model Development Platform teams in the UK and US.
• Identify capability gaps and build the technical and organisational case to address them.

Requirements

• 8+ years of experience in machine learning engineering, including hands-on computer vision using camera or lidar data.
• Demonstrated experience shipping production machine learning systems.
• 2+ years of experience managing or technically leading senior engineers.
• Staff-level depth in transformers, multimodal systems, foundation models, and large-scale training.
• Proficiency in Python and PyTorch or a similar framework, with strong judgement about production-grade machine learning.
• Ability to align roadmaps across teams and geographies and communicate technical strategy clearly to senior stakeholders.

Nice to have

• Experience with 3D scene understanding, offline models, simulation, counterfactual evaluation, or distributed teams.

Culture & Benefits

• Relocation support and visa sponsorship are available where applicable.
• Hybrid working with access to vehicle workshops and labs.
• Learning and development support.
• Meaningful equity and salaries benchmarked against the market annually.
• Location-dependent health, family, pension, and wellbeing benefits.
• An environment with significant ownership, where processes and structure are still being developed.

Hiring process

• 25-minute initial recruiter call.
• 60-minute hiring manager domain chat.
• Four hours of deep-dive interviews covering ML architecture, systems, and domain expertise.
• 45-minute final interview focused on mission and values alignment.