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Computer Science Research Intern Jobs in San Rafael, CA

Labelbox

Applied Research Intern

San Francisco, CA

Role Overview As an Applied Research intern at Labelbox, you will design, build, and productionize ... D. or Master's degree in Computer Science, Machine Learning, AI, or a related field (in progress ...

Alljoined

Research Intern (Fall)

San Francisco, CA · On-site

$30/hr

About the Role As a Research Intern , you will contribute to building the computational ... About You * Currently pursuing or recently completed a degree in Computer Science, Software ...

Labelbox

Applied Research Intern

San Francisco, CA · On-site

Role Overview As an Applied Research intern at Labelbox, you will design, build, and productionize ... D. or Master's degree in Computer Science, Machine Learning, AI, or a related field (in progress ...

Phonic

Research Intern (Fall 2026)

San Francisco, CA · On-site

The Role As a Research Intern at Phonic, you'll work directly on the core problems that make Phonic ... Work directly with research scientists and engineers to move fast from prototype to production

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Computer Science Research Intern information

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How much do computer science research intern jobs pay per month?

As of Jul 10, 2026, the average monthly pay for computer science research intern in San Rafael, CA is $7,178.17, according to ZipRecruiter salary data. Most workers in this role earn between $4,925.00 and $8,550.00 per month, depending on experience, location, and employer.

What does a Computer Science Research Intern do?

A Computer Science Research Intern typically assists with research projects in areas like artificial intelligence, data science, software engineering, or cybersecurity. Their responsibilities may include reviewing academic literature, designing and running experiments, analyzing data, and writing reports or research papers. Interns often collaborate with faculty members, graduate students, or research teams to solve real-world problems and contribute to new technological advancements. The experience helps interns gain practical skills, deepen their technical knowledge, and prepare for future careers in academia or industry.

What are the typical responsibilities of a Computer Science Research Intern during a project cycle?

As a Computer Science Research Intern, you’ll often be involved in conducting literature reviews, designing and implementing experiments, collecting and analyzing data, and presenting your findings to the research team. Interns frequently collaborate with senior researchers and other interns, participate in regular meetings, and may contribute to academic papers or technical documentation. This hands-on role provides valuable exposure to the research process in a professional setting, helping you build both technical and communication skills.

What are the key skills and qualifications needed to thrive as a Computer Science Research Intern, and why are they important?

To thrive as a Computer Science Research Intern, you need a solid understanding of algorithms, data structures, programming languages (such as Python, Java, or C++), and a strong academic background in computer science or related fields. Familiarity with research tools like LaTeX, version control systems (e.g., Git), and experience with data analysis or machine learning frameworks is often required. Strong analytical thinking, curiosity, effective communication, and the ability to collaborate within a research team are highly valued soft skills. These skills and qualities enable interns to contribute meaningfully to research projects, solve challenging problems, and communicate findings clearly.
What job categories do people searching Computer Science Research Intern jobs in San Rafael, CA look for? The top searched job categories for Computer Science Research Intern jobs in San Rafael, CA are:
What cities near San Rafael, CA are hiring for Computer Science Research Intern jobs? Cities near San Rafael, CA with the most Computer Science Research Intern job openings:
Computer Science Research Intern jobs near you
Applied Research Intern

Applied Research Intern

Labelbox

San Francisco, CA

Other

Re-posted 6 days ago

Job description

Role Overview

As an Applied Research intern at Labelbox, you will design, build, and productionize evaluation and posttraining systems for frontier LLMs and multimodal models. You'll own continuous, high-quality evals and benchmarks (reasoning, code, agent/tooluse, longcontext, visionlanguage, et al.), create and curate posttraining datasets (human + synthetic), and prototype RLHF/RLAIF/RLVR/RM/DPOstyle training loops to measure and improve realworld task and agent performance.

Your Impact
  • Build and own evaluation and benchmark suites for reasoning, code, agents, longcontext, and V/LLMs.
  • Create posttraining datasets at scale: design preference/critique pipelines (human + synthetic), and target hard failures surfaced by evals.
  • Experiment and prototype RLHF/RLAIF/RLVR/RM/DPOstyle training loops to improve real-world task and agent performance.
  • Land research in product: ship improvements into Labelbox workflows, services, and customerfacing evaluation/quality features; quantify impact with customer and internal metrics.
  • Engage with customer research teams: run pilots, codesign benchmarks, and share practical findings through internal research reports, blog posts, talks, and published papers.
What You Bring
  • A strong foundation in AI and machine learning, backed by a Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field (in progress degrees are acceptable for intern positions).
  • A deep understanding of frontier autoregressive and diffusion multimodal models, along with the human and synthetic data strategies needed to optimize them.
  • Passion and experience for LLM evaluation and benchmarking.
  • Expertise in training data quality construction, measurement and refinement.
  • The ability to bridge research and application by interpreting new findings and translating them into functional prototypes.
  • A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.
  • Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow.
  • Exceptional communication and collaboration skills.
Applied Research at Labelbox

At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advancing human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.

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