Coinbase: Machine Learning Engineer Intern — Hybrid - San Francisco, CA

About Coinbase

Coinbase works on digital-asset and financial technology, with its recruitment material discussing an open financial system and crypto-related markets. Its advertised business activities connect consumer and business products with engineering, financial operations and regulated-market development. The company describes local product initiatives alongside the compliance, policy and operational work needed to support them. This gives the business both a technology dimension and a financial-services context, with product delivery linked to the requirements of the markets in which it operates.

The position and its setting

Coinbase lists Machine Learning Engineer Intern in Hybrid - San Francisco, CA, under reference 8175441. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Internships & Emerging Talent Positions
• Employer listing date: 9 September 2026

Responsibilities and work described

• Develop, deploy, and operate machine learning models and pipelines at production scale
• Drive an end-to-end research project applying modern ML techniques to solve a defined business problem
• Partner with senior engineers and product teams to identify new ML applications for blockchain and crypto use cases
• Present findings and recommendations to cross-functional stakeholders at the conclusion of your internship
• Required Skills and

Essential requirements and candidate background

• Currently pursuing a Ph.D. with published or in-progress research in machine learning, deep learning, or a closely related field
• Demonstrated proficiency building and training models using ML frameworks such as PyTorch or TensorFlow
• Experience applying ML techniques including supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets
• Familiarity: software engineering fundamentals including version control, testing, and writing production-quality Python code
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality
• Req ID: P78143
• #LI-Hybrid
• Pay Transparency Notice: Depending on your work location, the target hourly rate for this position can range as detailed below
• Hourly Rate:
• $60 — $60 USD
• Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period
• US Applicants: View Employee Rights, Know Your Rights, and E-Verify Notice of Participation
• Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com
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• Data Privacy & Arbitration: By submitting your application, you agree to our Candidate Privacy Notice
• US applicants: By submitting your application, you agree to Arbitration of Disputes

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Advertised location: Hybrid - San Francisco, CA

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Machine Learning Engineer Intern vacancy is not an offer for reference 8175441; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Coinbase

Applications follow the official employer page linked below.

Open the official Coinbase posting below and match the title and reference 8175441.

Compare your qualifications and experience with the essential conditions for the Hybrid - San Francisco, CA position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• AI/ML
• machine learning
• AI
• training
• stakeholder management