Staff Research Engineer — Vision-Language Autonomy

Rivian; Palo Alto (CA); On-site; USD 265,000 - 331,300; Full time

Benefits offered by this job

401(k) Plan

Employee Stock Purchase Program

Paid vacation

Paid sick leave

Job summary

Rivian seeks a Staff Research Engineer to shape the Vision‑Language Models (VLMs) strategy for its Autonomy stack. You will own end‑to‑end lifecycle of VLM model delivery—from data acquisition and metrics to deployment and feedback loops—across multi‑modalities and novel use cases.

You will partner with Perception, Planning and Calibration teams to translate vehicle feature needs into robust ML solutions and optimizations.

Qualifications

• Education in CS/Robotics/related quantitative field (BS/MS/PhD).
• 5+ years scaling ML solutions with VLM/LLM techniques.
• Experience in data mining, long-tail distributions and anomaly detection.
• Proficiency in Python and ML pipelines; strong perception awareness.
• Ability to diagnose complex issues across distributed systems.

Responsibilities

• Define and execute the VLM model delivery roadmap including training, deployment and multi‑modal extensions.
• Design data mining strategies for long-tail distributions and anomaly detection at scale.
• Establish rigorous evaluation benchmarks and diagnose system performance issues.
• Collaborate with Autonomy teams to translate vehicle features into ML deliverables.
• Make trade-offs and define cross‑functional requirements for VLM systems.

Skills

VLM model training

Large-scale data mining

Zero/few-shot learning

System engineering

Execution & debugging

Education

BS/MS/PhD in Computer Science, Robotics, EE

Tools

Python

TensorRT

Benchmarking tools

ML infrastructure

Job description

Rivian seeks a Staff Research Engineer to shape the Vision‑Language Models (VLMs) strategy for its Autonomy stack. You will own end‑to‑end lifecycle of VLM model delivery—from data acquisition and metrics to deployment and feedback loops—across multi‑modalities and novel use cases.

You will partner with Perception, Planning and Calibration teams to translate vehicle feature needs into robust ML solutions and optimizations.