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Full Stack Engineering Intern Summer 2026

San Francisco,...
E

Ember

Startup
Category
Technical
Experience
0-3 years
Type
Internship
Location
San Francisco, CA, US
Salary
$6,000 - $10,000
Job Description
Benefits & Culture
Paid Internship
Core Values
Passion
Curiosity
Collaboration
This goes straight to the founder
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No recruiters. Founders reply directly.

Founder Signals
Response Rate
85%
Avg Response Time
2 hours
Compensation Calculator
In startups, higher salary usually means lower equity.
Salary (affects equity %)
Link salary ↔ equity
$125,000
$6,000$10,000
Equity % (auto from trade-off model)
0.51%
0%5%
Projected Exit Value
$350,000,000
$10M$500M
Live Trade-off
Salary
Equity %
Est. Equity Value at Exit
$100,000
0.51%
$892,500
$125,000
0.51%
$892,500
$150,000
0.51%
$892,500
$175,000
0.51%
$892,500

Advanced Salary & Equity Calculator

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What You’ll Do

  1. Lead the design and implementation of end-to-end features across our web applications and backend services.
  2. Build internal evaluation infrastructure for ML and LLM healthcare applications.
  3. Architect and maintain scalable, secure, and reliable systems that integrate with various healthcare platforms.
  4. Drive best practices in software development, including code reviews, testing, and documentation.

Qualifications

  1. Currently pursuing a Bachelor's or Master’s degree in Computer Science, Software Engineering, or a related technical field.
  2. Proficiency in TypeScript, React, Node.js, and Python.
  3. Comfortable with LLM applications and containerized deployments.
  4. Thrives in environments of complexity and ambiguity, prioritizing collaboration and seeking the best ideas regardless of their source.
  5. A willingness to pitch in wherever needed—we move fast, and we need team players who are eager to contribute.

Bonus

  1. Hands-on work with LLM prompt engineering, finetuning, and RAG applications.
  2. Experience with workflow automations.
  3. Prior work in healthcare, clinical AI, or other regulated, high-stakes industries.
  4. Open-source contributions to ML libraries, evaluation suites, or benchmarking tools.
  5. Experience with cloud platforms (e.g., Azure, GCP, AWS) and containerization technologies (e.g., Docker, Kubernetes).
  6. Strong understanding of database systems, both relational and non-relational.
  7. Familiarity with healthcare standards such as FHIR, HL7, and medical coding.