TL;DR

Senior Machine Learning Engineer (AI): Develop and implement advanced large language and vision models (LLM/VLM) for spatial-temporal visual reasoning in autonomous driving. Focus on designing robust training pipelines, evaluation metrics, and optimizing model performance with techniques like supervised fine-tuning and reinforcement learning.

Location: Hybrid in Mountain View or San Francisco, California, United States

Salary: $204,000–$259,000 USD

Company

%hirify_global% is a leading autonomous driving technology company focused on building the world's most experienced and trusted self-driving system.

What you will do

Design and implement models and algorithms for visual reasoning using LLM/VLM in autonomous driving scenarios.
Develop and maintain training and evaluation pipelines focused on decision-making rationale and question answering.
Collaborate with engineers and researchers to integrate visual reasoning into product systems.
Lead data curation and establish evaluation metrics for large-scale rationale/QA datasets.
Apply advanced techniques like supervised fine-tuning and reinforcement learning to improve model performance.
Analyze sensor data to identify challenges and opportunities for model enhancement in real-world environments.

Requirements

Must have 5+ years of experience in machine learning with large-scale model development (LLM, VLM, or similar).
Strong coding skills in Python and deep learning frameworks such as Jax, TensorFlow, and PyTorch.
Experience with model training, evaluation, and deployment in production environments.
Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent experience.
Location: Hybrid role based in Mountain View or San Francisco, California, United States.

Nice to have

Experience with supervised fine-tuning and reinforcement learning for language/vision models.
Familiarity with large-scale multimodal data curation and quality assurance.
Background in autonomous vehicle perception, motion planning, or decision-making systems.
Publications in top-tier ML or computer vision conferences.
PhD in a relevant field.