Machine Learning Engineer (Perception LLM/VLM)

TL;DR

Machine Learning Engineer (Perception LLM/VLM): Developing and optimizing large-scale continual pre-training pipelines for cutting-edge VLM foundation models with an accent on multimodal data integration and autonomous driving perception. Focus on designing novel pre-training techniques, evaluating model performance at scale, and translating research into production-ready systems for the hirify.global Driver.

Location: Must be based in Mountain View or San Francisco, California

Salary: $170,000–$216,000 USD

Company

hirify.global is an autonomous driving technology company dedicated to building the world's most trusted driver to improve mobility and safety.

What you will do

• Design, implement, and optimize large-scale continual pre-training pipelines for VLM foundation models.
• Conduct research on novel pre-training techniques to integrate diverse, multimodal sensor data.
• Develop and evaluate metrics for measuring foundation model performance in autonomous driving contexts.
• Collaborate with downstream teams on system integration and optimization for onboard and offboard hardware.
• Translate cutting-edge research in LLMs, VLMs, and continual learning into production-ready systems.

Requirements

• 5+ years of experience in Machine Learning with a focus on large-scale foundation models.
• Proven expertise in LLM/VLM pre-training and continual learning with large datasets.
• Strong coding proficiency in Python and deep learning frameworks like Jax, TensorFlow, or PyTorch.
• Hands-on experience with model training, evaluation, and deployment in production environments.
• Master's degree in Computer Science, Electrical Engineering, or a related field.

Nice to have

• Experience in fine-tuning foundation models for autonomous driving or robotics.
• Background in autonomous vehicle perception, motion planning, or decision-making.
• PhD in a relevant field.
• Publications in top-tier ML or computer vision conferences (e.g., NeurIPS, CVPR).

Culture & Benefits

• Participation in a discretionary annual bonus program.
• Equity incentive plan eligibility.
• Comprehensive company benefits program.
• Opportunity to work with millions of miles of real-world driving data.
• Collaborative environment with research teams at Alphabet.