Senior/Staff Engineer, Machine Learning - Online Mapping (Autonomous Driving)

Location: Mountain View, California, United States

Salary: $183,825–$333,925 base pay annually, plus annual performance bonus, equity, and benefits.

Company

hirify.global is a physical AI company developing Level 4 autonomous driving technology and a universal autonomy platform for robotaxis, logistics fleets, and personal vehicles.

What you will do

• Research, develop, and implement online mapping models and algorithms for autonomous vehicles.
• Build robust machine learning and mapping systems using real-world camera, LiDAR, and other sensor data.
• Analyze online mapping performance and identify improvements to architecture, data, and evaluation in end-to-end ML systems.
• Build and optimize ML pipelines and productize machine learning models.
• Integrate models into centralized architectures with other machine learning teams.
• Collaborate with autonomy, infrastructure, and systems stakeholders on mapping requirements.

Requirements

• Proven experience solving production machine learning problems and balancing data, model, and evaluation trade-offs.
• Strong understanding of machine learning fundamentals and hands-on experience training and evaluating modern models in autonomous vehicles, robotics, mapping, computer vision, or related fields.
• Experience with robotics-related ML applications, 3D geometry, and state estimation.
• Strong Python skills and experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience working with complex multi-component systems and optimizing ML models.
• Ability to iterate quickly, make data-driven decisions, and deliver practical solutions on schedule.

Nice to have

• Familiarity with distributed training and ML compilers.
• Research publications in leading conferences such as NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, or ICRA.

Culture & Benefits

• Base compensation is complemented by an annual performance bonus, equity, and a competitive benefits package.
• Inclusive workplace focused on diversity and psychological safety.
• Opportunity to contribute to autonomous driving technology for logistics and transportation.