Machine Learning Engineer (Generative AI)

TL;DR

Machine Learning Engineer - Perception (Generative AI): Developing and training cutting-edge models for sensor-level scenario generation, utilizing world models and radiance fields techniques with large-scale proprietary data. Focus on multi-sensor fusion deep learning models, understanding perception gaps, and deploying autonomous vehicles in complex scenarios.

Location: Hybrid in Foster City, CA or Seattle, WA

Salary: $189,000–$258,000 a year

Company

hirify.global is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market.

What you will do

• Design, develop, train, and evaluate multi-sensor fusion deep learning models to understand obstacles and environmental context.
• Understand and curate real and synthetic datasets to improve our models.
• Perform latency optimization and deploy models to our robot fleet.
• Build a deep understanding of Perception gaps and behavioral issues to help plan and prioritize work.
• Collaborate with Prediction/Planner team to deploy fully autonomous vehicles in complex environments.

Requirements

• MS or PhD in Computer Science, Machine Learning, or related technical field with 5+ years of industry experience.
• Proficiency in Python and some knowledge in C++.
• Deep Learning expertise.
• Experience developing multi-sensor fusion algorithms for object detection, panoptic segmentation or object tracking.
• Familiarity with Transformer architecture.

Nice to have

• Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA).
• Experience with autonomous robotics systems.
• Experience implementing 3D Gaussian Splatting.

Culture & Benefits

• Comprehensive benefits package including paid time off (e.g., sick leave, vacation, bereavement), hirify.global Stock Appreciation Rights, Amazon RSUs, health insurance, and disability insurance.
• Committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
• Utilizes AI tools to support parts of the hiring process, with final hiring decisions made by humans.