Staff Software Engineer, Perception (Autonomous Driving)

Location: Hybrid work from hirify.global offices in Mountain View, CA; Pittsburgh, PA; or Seattle, WA, with at least 3 days per week in the office.

Salary: $189,000–$303,000 per year for Mountain View and Seattle roles; $171,000–$273,000 per year for Pittsburgh roles. Additional annual bonus, equity compensation, and benefits are available.

Company

Build self-driving technology and transportation solutions intended to make mobility and logistics safer, more efficient, and more accessible.

What you will do

• Address end-to-end perception challenges involving dynamic actor tracking, action and attribute recognition, and semantic understanding of traffic environments.
• Research and develop deep learning and machine learning models for highway, urban, long-range multisensor, and degraded-sensor scenarios.
• Design object-tracking algorithms and fuse complementary information from multiple sensors.
• Develop production-ready perception software and ML systems for the real-time hirify.global Driver platform.
• Build and improve large-scale model training pipelines, analyze failure modes, and implement tested solutions.
• Contribute to perception architecture and collaborate across engineering, on-road testing, and simulation teams.

Requirements

• Master’s degree or higher in Computer Science, Robotics, Electrical Engineering, or a related field, or a bachelor’s degree with 2+ years of relevant software engineering experience.
• Proficiency in C++ and Python, with experience writing clean, scalable, efficient, production-quality code.
• Working knowledge of machine learning areas such as deep learning, computer vision, recursive state estimation, structured prediction, or optimization.
• Experience with PyTorch, TensorFlow, or another deep learning framework.
• Authorization to work lawfully in the United States is required; visa sponsorship may be required depending on the candidate’s status.

Nice to have

• Experience deploying computer vision or ML models in real-time computing environments.
• Knowledge of optimization, supervised and unsupervised learning, generative and discriminative methods, and Hidden Markov Models.
• Experience with VLMs, foundation or world models, CUDA, or high-performance GPU programming.
• Robotics, computer vision, self-driving experience, relevant publications, open-source contributions, or ML workflow automation experience.

Culture & Benefits

• Hybrid work environment with regular in-person collaboration.
• Annual bonus, equity compensation, and employee benefits.
• Culture centered on safety, integrity, collaboration, inclusion, and long-term impact.
• Commitment to reasonable accommodations and an inclusive hiring process.