Manager, Multi-Modal LLM Applications

Job Description

Zoox is developing the first fully autonomous, purpose-built electric vehicle designed for autonomous ride-hailing. We are a passionate, collaborative, and fast-moving team working to build a revolutionary new mobility experience. This role offers the opportunity to make critical contributions to a challenging and groundbreaking product.

Zoox is seeking an experienced Manager of Multi-Modal LLM Applications to lead a team focused on applying cutting-edge Large Multi-Modal Models (MLLMs) to solve concrete, offline autonomy problems. This role is crucial for deploying state-of-the-art AI into our autonomous driving platform, directly impacting the safety and performance of our technology.

Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

In this role, you will

Leadership: Lead and manage a team of talented Machine Learning Engineers specializing MLLMs for concrete applications.

Model Development & Deployment: Oversee the full lifecycle of MLLM development, with a specific focus on post-training methodologies (e.g., fine-tuning, RLHF, context engineering) to optimize models for autonomy tasks.

Internal Customer Focus: Drive the deployment of complex MLLM solutions to internal customers, specifically solving tangible offline autonomy problems within the Zoox ecosystem.

Cross-Functional Strategy: Understand and identify dependencies between your team's work and other engineering teams and domains (e.g., Perception, Prediction, Planning, Validation). Collaborate with functional peer managers to ensure alignment and cooperation.

People Management & Development: Proactively create development opportunities for team members, coaching and mentoring them to grow their technical and leadership skills. Estimate staffing needs and schedules and assign project work to drive efficiency and meet operational goals.

Operational Execution & Problem Solving: Establish team goals and priorities and execute against operational needs. Apply and improve upon existing processes and procedures to resolve functional problems for the team.

Identify issues, gather facts, and execute analysis of situations or data to inform strategy and decisions.

Accountability & Influence: Your decisions will have a lasting impact on the success of the team and department. You will be responsible for managing special projects and initiatives and will frequently conduct presentations of key information to gain the cooperation of others.

Strategic Influence: Leverage broad knowledge of the specialized field/discipline to analyze complex information. Recommend and collaborate with senior management to resolve strategic issues. This role may involve leading a medium-to-large team, including direct reports who are also managers.

Qualifications

5+ years of professional experience in Machine Learning or Deep Learning, with a focus on large-scale model applications.

3+ years of experience leading and managing engineering or research teams focused on AI/ML.

Direct experience leading teams training Multi-Modal Large Language Models (MLLMs), with deep expertise in post-training techniques (e.g., instruction tuning, alignment, domain adaptation).

Proven track record of deploying ML/MLLM models to production or internal customers to solve complex, real-world problems, ideally within the autonomy or robotics domain.

Strong organizational skills to manage complex project schedules, staffing needs, and priorities effectively.

A passion for mentoring and developing high-performing team members.

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