Senior Machine Learning Engineer (Autonomous Driving)

Location: Sunnyvale, California, USA; hybrid work with in-person collaboration and remote working time.

Salary: $311,850–$389,400 per year for the senior level.

Company

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

What you will do

• Build, train, and fine-tune scene-understanding models for offline measurement of driving performance.
• Adapt on-vehicle architectures and foundation models for offline use with larger compute budgets and bidirectional temporal context.
• Improve model accuracy and generalisation across vehicle platforms, geographies, and driving conditions.
• Benchmark models, diagnose failure modes, and use error analysis to guide iteration.
• Define quality bars and statistically credible evidence for validation pipelines and safety cases.
• Collaborate with modelling, evaluation, data curation, and simulation teams while mentoring other engineers.

Requirements

• 4+ years of machine-learning engineering experience, including training and shipping deep-learning models in production.
• Hands-on experience with computer vision, transformer, multimodal, or vision-language architectures.
• Experience adapting or fine-tuning pretrained or foundation models and understanding data, loss, and representation trade-offs.
• Proficiency in Python and PyTorch or a similar framework, with experience in large-scale training.
• Ability to take ambiguous modelling problems from scoping through to measurable solutions.
• Experience in 3D scene understanding, offline modelling, auto-labelling, temporal or world models, autonomous vehicles, robotics, or distributed training is valuable.

Nice to have

• Experience with 3D scene understanding, offline modelling, auto-labelling, temporal or world models, autonomous vehicles, robotics, or distributed training.

Culture & Benefits

• Hybrid work with access to vehicle workshops and laboratories.
• Relocation support and visa sponsorship where applicable.
• Meaningful equity and salaries benchmarked annually against the market.
• Learning and development support.
• Location-dependent health, family, retirement, and wellbeing benefits.
• An evolving working environment with substantial individual ownership.

Hiring process

• 25-minute recruiter screen.
• 60-minute competency interview followed by three hours of technical interviews covering applied machine learning, system design, and programming.
• 60-minute final interview focused on mission and values alignment.