Manager, Multi-Modal Language Action Models
Leads a team of ML engineers applying multi-modal large language models to solve autonomy problems, overseeing development, deployment, and post-training optimization like fine-tuning and RLHF. Requires 5+ years ML experience and 3+ years managing AI teams, with expertise in MLLMs.
About the job
Responsibilities
- Lead and manage a team of Machine Learning Engineers specializing in MLLMs for autonomy applications.
- Oversee the full lifecycle of MLLM development, focusing on post-training methodologies (e.g., fine-tuning, RLHF, context engineering) to optimize for autonomy tasks.
- Drive deployment of MLLM solutions to internal customers, solving offline autonomy problems.
- Identify dependencies with other teams (e.g., Perception, Prediction, Planning, Validation) and collaborate with peer managers.
- Create development opportunities, coach, and mentor team members; estimate staffing and assign projects.
- Establish team goals, execute operations, improve processes, and solve problems through analysis.
- Manage special projects, present information, and influence senior management on strategic issues.
Qualifications
- 5+ years professional experience in Machine Learning or Deep Learning, focusing on large-scale model applications.
- 3+ years leading AI/ML engineering or research teams.
- Direct experience leading teams training Multi-Modal Large Language Models (MLLMs), with expertise in post-training techniques (e.g., instruction tuning, alignment, domain adaptation).
- Proven track record deploying ML/MLLM models to production/internal customers for complex real-world problems, ideally in autonomy/robotics.
- Strong organizational skills for managing schedules, staffing, and priorities.
- Passion for mentoring high-performing team members.
Skills
Multi-Modal Large Language Models, Machine Learning, Deep Learning, RLHF, Fine-Tuning, Instruction Tuning, Alignment, Domain Adaptation, Autonomous Driving, Production Deployment
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