AI Research Intern
OpusClip · Mountain View, CA
$52,000–$58,240
Jul 21, 2026
Mountain View, CA
Jul 23, 2026
What this job asks for AI summary
An internship on the AI research team, focused on developing and evaluating deep learning models across computer vision, speech, multimodal systems, and large language models. Day-to-day work spans building research prototypes, integrating foundation models into production features, and designing evaluation pipelines. Suited to Master's-level candidates with hands-on experience in at least one of low-level vision, speech processing, or LLM fine-tuning.
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 260 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (data scientists). range 65–340
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).
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 (10)
This is an internship role; the posting does not specify a duration or compensation.
The role is described as 'flexible remote/on-site' with 3 days/week on-site required and 4+ days preferred — it is not fully remote. The company is headquartered in Mountain View, CA (San Jose-Sunnyvale-Santa Clara CBSA).
A Master's degree in CS, AI, Mathematics, or a related field is listed under Basic Qualifications but framed as 'currently pursuing or recently completing,' which is typical internship language rather than a hard degree gate; the degree requirement is set to None accordingly.
The SOC is a close call between 15-2051 (Data Scientists, reflecting the ML/modeling/research focus) and 15-1252 (Software Developers, reflecting the applied AI engineering and production-shipping responsibilities). The research-first framing and emphasis on model development, benchmarking, and ML techniques tips the balance to 15-2051.
Deep learning foundations (Transformer architecture, attention mechanisms, generative model families) are listed under Basic Qualifications as required conceptual knowledge; they are captured as the required/preferred flag skills. The specific model architectures (Real-ESRGAN, SwinIR, etc.) and fine-tuning techniques (SFT, RLHF/DPO, LoRA/PEFT) appear under 'Hands-on Experience in One or More of the Following,' which is a partially-required section — marked as preferred since only one area is needed.
LangChain and RAG appear in the narrative description of applied AI engineering work rather than under a formal requirements heading — marked as preferred.
TypeScript is explicitly called 'a bonus' in the Preferred Qualifications section.
Publications and open-source contributions are mentioned as pluses under Preferred Qualifications; they name no specific technology and are omitted from the skills list per extraction rules.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Transformer architecture.
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
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