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Fall Computer Science Internships Jobs in Berkeley, CA

Faire

Data Science Intern

San Francisco, CA · On-site

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform ... in Computer Science, Operations Research, Statistics, Econometrics, or a related technical ...

Astranis

FPGA Intern (Fall 2026)

San Francisco, CA

FPGA Intern (Fall 2026) Internships at Astranis typically last for twelve weeks, and are hourly ... S. or M.S. in electrical engineering, computer science, computer engineering, or equivalent * A ...

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Fall Computer Science Internships information

What are the key skills and qualifications needed to thrive in Fall Computer Science Internships, and why are they important?

To thrive in Fall Computer Science Internships, you typically need a solid understanding of programming fundamentals, data structures, algorithms, and current enrollment in a computer science or related degree program. Familiarity with coding languages like Python, Java, or C++, and experience with collaborative tools like Git or project management systems are often expected. Strong problem-solving abilities, effective communication, and the ability to work well in teams help interns stand out. These skills and qualifications enable interns to contribute meaningfully to projects and maximize learning in a professional tech environment.

What are Fall Computer Science Internships?

Fall Computer Science Internships are temporary positions offered by companies, organizations, or academic institutions to students or recent graduates during the fall semester. These internships provide hands-on experience in software development, programming, data analysis, or related computer science fields. Interns typically work on real-world projects under the guidance of experienced professionals, gaining valuable technical skills and industry exposure. Fall internships can enhance your resume, expand your professional network, and sometimes lead to full-time job offers after graduation.

What types of projects do Fall Computer Science Interns typically work on, and how is mentorship structured?

Fall Computer Science Interns commonly work on real-world projects that align with the company's ongoing initiatives, such as developing new software features, debugging existing applications, or contributing to team-based research. Mentorship is usually provided through a designated supervisor or a buddy system, offering regular check-ins, code reviews, and guidance on both technical and professional growth. Interns are encouraged to collaborate closely with other engineers, attend team meetings, and actively participate in brainstorming sessions, which helps them build valuable skills and expand their professional network.
What job categories do people searching Fall Computer Science Internships jobs in Berkeley, CA look for? The top searched job categories for Fall Computer Science Internships jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Fall Computer Science Internships jobs? Cities near Berkeley, CA with the most Fall Computer Science Internships job openings:
Fall Computer Science Internships jobs near you
Infographic showing various Fall Computer Science Internships job openings in Berkeley, CA as of June 2026, with employment types broken down into 33% Internship, and 67% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.
Data Science Intern

Data Science Intern

Faire

San Francisco, CA • On-site

$75/hr

Other

Posted 19 days ago

Job description

Data Science Internship - Fall 2026

Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e-commerce platforms and big-box stores. Our Data Science team builds and maintains the algorithmic systems - spanning search, personalization, recommendation, and ranking - that power our marketplace and help our customers thrive.

We are hiring Data Science interns across several teams and are looking for intellectually curious, self-directed problem solvers eager to work end-to-end on high-impact challenges, from data exploration to production-ready solutions.

Our internships are paid, 12-14 weeks in duration, with flexible start dates. Extensions are considered based on project scope and mutual interest.

Open Team

Search & Recommendation

  • Design and deploy state-of-the-art recommender systems that power ranking and discovery across the marketplace
  • Develop rich user and item representations through embeddings, sequence models, and graph-based methods
  • Build real-time and streaming data pipelines that enable dynamic, context-aware personalization at scale
  • Apply exploration-exploitation strategies - including contextual bandits and reinforcement learning - to optimize recommendations under uncertainty
  • Advance recommendation quality through improvements to diversification, novelty, and long-term user engagement
  • Own the full ML lifecycle: from problem formulation and modeling through offline evaluation and online experimentation

What You'll Do

  • Design, develop, and A/B test cutting-edge machine learning algorithms and analytical solutions, with guidance from senior technical leads
  • Communicate project objectives, methodologies, and results clearly to both immediate teammates and broader cross-functional stakeholders
  • Navigate the complexity of a two-sided marketplace, identifying and addressing the unique challenges that arise at the intersection of retailer and brand needs

What We're Looking For

All candidates must be currently enrolled or recently graduated Master's or PhD students in Computer Science, Operations Research, Statistics, Econometrics, or a related technical discipline. Beyond that, we're looking for team-specific experience:

Search & Recommendation Systems

  • Publications or submissions to top-tier venues such as KDD, RecSys, ICML, NeurIPS, WWW, or SIGIR
  • Experience with recommender systems (collaborative filtering, deep recommenders, ranking), representation learning and embeddings, sequential models (RNNs, Transformers for user behavior modeling), bandit and reinforcement learning methods, and large-scale retrieval and ranking systems
  • Familiarity with offline evaluation metrics (NDCG, MAP, recall) and online experimentation
  • Experience working with large-scale or production datasets

Pay rate:

San Francisco: the pay rate for this role is $75 USD per hour.

Actual hourly pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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