Principal Engineer (3D Computer Vision)

Location: Sunnyvale, California, USA; hybrid working model with in-person collaboration in office spaces, remote work, and hands-on work in vehicle workshops and labs.

Salary: $370,040–$419,800 annually.

Company

hirify.global develops an AI platform for autonomous driving, using mapless, hardware-agnostic vehicle intelligence that learns from real-world driving experience.

What you will do

• Set technical direction for geometric vision and develop 3D foundation models and world models from large-scale driving data.
• Design architectures for 3D perception, geometric reasoning, reconstruction, and scene dynamics across space and time.
• Build scalable data-generation, auto-labeling, ground-truth, and evaluation pipelines using camera, radar, LiDAR, and other sensor data.
• Develop offline SLAM, structure-from-motion, calibration, and 3D reconstruction systems for model training and evaluation.
• Explore multi-view geometry, neural rendering, NeRFs, Gaussian Splatting, implicit representations, video modeling, and geometry-aware tokenization.
• Train, evaluate, optimize, and deploy models on distributed compute and resource-constrained autonomous-driving hardware.

Requirements

• Deep expertise in 3D computer vision, geometric vision, or 3D machine learning.
• Experience designing, training, and evaluating modern deep-learning models at scale with PyTorch or a comparable framework.
• Strong foundations in geometry, linear algebra, probability, optimization, and 3D transformations.
• Excellent software engineering skills in Python and C++.
• Experience taking difficult research problems from concept to working systems, including large-scale data, training, evaluation, or deployment pipelines.
• Principal-level technical leadership, architectural decision-making, and cross-team technical direction.

Nice to have

• Experience with neural fields, NeRFs, Gaussian Splatting, feedforward 3D models, or dense reconstruction.
• Experience with vision pre-training, self-supervised learning, video models, generative models, or learned scene dynamics.
• Experience with multimodal sensor fusion, distributed training, large-scale experimentation, or real-time ML deployment.

Culture & Benefits

• Hybrid work combining office collaboration with focused remote work.
• Market-benchmarked salaries, meaningful equity, and location-dependent benefits.
• Relocation support and visa sponsorship where applicable.
• Learning and development budgets for training, conferences, and professional growth.
• Health and dental insurance, enhanced parental leave, retirement or pension benefits where applicable, therapy access, wellbeing partnerships, and team socials.

Hiring process

• Initial recruiter call lasting 30 minutes.
• Competency interviews covering hiring management and applied machine learning, followed by deep-dive interviews in programming, systems design, and technical leadership.
• Final 45-minute mission and values interview with a Director or VP.