Machine Learning Engineer (ADAS)

TL;DR

Machine Learning Engineer (ADAS): Developing and optimizing computer vision and 3D perception models for autonomous driving systems with an accent on end-to-end ML lifecycle management and scalable data pipelines. Focus on building detection, classification, and instance segmentation capabilities that operate under real-world product constraints.

Location: Must be based in or able to relocate to London, UK (Hybrid model).

Company

hirify.global is a leading developer of Embodied AI technology, creating mapless and hardware-agnostic foundation models for autonomous driving.

What you will do

• Train, debug, and improve computer vision and 3D perception models.
• Build and maintain scalable data pipelines, including auto-labelling and pseudo-labelling.
• Iterate on models based on performance evaluation signals and system underperformance.
• Contribute to offline pipelines such as tracking and 3D reconstruction.
• Partner with cross-functional teams to define technical priorities and model development strategies.

Requirements

• Proven experience shipping CV-focused deep learning systems.
• Strong applied ML engineering skills with experience in 3D perception concepts (e.g., LiDAR, multi-view geometry, tracking).
• Ability to own work end-to-end, including evaluation and dataset generation.
• Pragmatic problem-solving skills and experience working under real product constraints.
• Must be able to work in a hybrid model from the London office.

Nice to have

• Experience with latency-constrained on-car model development.
• Background in large-scale data generation and offline model training.

Culture & Benefits

• Meaningful equity in the company.
• Relocation support and visa sponsorship where applicable.
• Hybrid working model with core hours.
• Comprehensive health insurance, dental, and wellbeing partnerships.
• Learning and development budgets for training and conferences.

Hiring process

• Initial recruiter screen (30 mins).
• Competency interviews: Programming and System Design (2 hours total).
• Deep-dive technical interview (1 hour).
• Final interview: Mission and values alignment (1 hour).