AI Research Engineer Intern
Renesas Electronics · San Jose, CA
$31.25–$47.75/hrfrom the description
Jul 19, 2026
San Jose, CA
Jul 21, 2026
What this job asks for AI summary
A hybrid internship (3–6 months, extendable) focused on building AI models for automotive driver-assistance systems. The work spans video-based driving scene understanding, causal reasoning, risk and trajectory prediction, and optimizing models for deployment on automotive edge hardware. It suits students in computer science, AI, or related fields with hands-on experience in deep learning frameworks and an interest in autonomous driving research.
Junior level · San Jose-Sunnyvale-Santa Clara, CA · Internship
“or” means any one of them counts — you don't need all of them.
Posted 3 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 320 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (data scientists). range 240–490
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $189,150 (middle half $152,859–$224,286). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role is an internship of 3–6 months (extendable), hybrid in San Jose, CA.
Candidates must be currently enrolled in a BS, MS, or PhD program — no completed degree is required as a hard gate, so the degree requirement is set to None.
The minimum qualifications list experience in 'one or more areas' from a broad menu (Autonomous Driving, LLMs, VLMs, VLA Models, World Models, Reinforcement Learning, Causal AI, Multi-modal Learning, Robotics, ONNX, TensorRT, Edge AI deployment). This is a single 'pick at least one' gate rather than a requirement for each named technology; LLMs is listed as the primary skill with the other named options captured as alternatives to represent this OR-logic.
PyTorch and TensorFlow are listed as an 'or' pair in the minimum qualifications; PyTorch is the primary with TensorFlow as the alternative.
ONNX and TensorRT appear both in the broad 'one or more areas' list (required section) and are individually called out in the responsibilities/deliverables context. They are also listed separately as preferred given the ambiguity of their placement within the broad menu.
The posting mentions bonus eligibility alongside the hourly range; the bonus amount is unspecified.
Posting is for a internship engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.