What You’ll Do
Join a Confidential Client engineering team as a New Grad Software Engineer and own customer-facing features from day one. You will:
- Build production-quality systems that process large volumes of data and ship reliable, scalable features.
- Work across the stack — backend services, data pipelines, and front-end interfaces — to deliver product outcomes.
- Collaborate with product managers and customers to define requirements, iterate quickly, and measure impact.
- Create tooling and infrastructure for evaluation, observability, and safe deployment of ML-driven applications.
- Design and implement matching, fraud-detection, and contributor-quality systems at scale.
- Contribute to UI/UX tooling paired with ML algorithms that support 100k+ contributors and billions of tasks.
Example Projects
- Build reinforcement-learning and post-training data pipelines to support frontier model development.
- Develop evaluation infrastructure that measures model reliability for enterprise and public-sector customers.
- Ship agentic AI applications and observability/testing tooling to keep deployments safe.
- Create fraud-detection and contributor-matching algorithms to ensure platform quality and throughput.
- Integrate ML models for customer workflows (e.g., churn prediction, RAG knowledge assistants) and build customer-facing services.
Qualifications
Minimum requirements:
- Graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in Computer Science, EECS, Computer Engineering, Statistics, or a closely related field.
- Product engineering experience building full-stack web apps, integrating with APIs/services, and shipping features end-to-end.
- Previous Product/Software Engineering internship experience.
- Demonstrated track record of shipping high-quality products or features at scale.
- Experience building systems that handle large volumes of data.
- Proficiency with Python and familiarity with TypeScript, React, and/or MongoDB.
Nice to Have
- Hands-on experience with large language models (LLMs), evaluation frameworks, or agentic systems from internships, research, or projects.
- Open-source contributions or a portfolio of shipped side projects.
- Experience with reinforcement learning data pipelines, model evaluation, or observability tooling.
Compensation & Benefits
- Employment type: Full-time.
- Base salary range for this position in San Francisco, CA: $124,000—$162,000 USD.
- Compensation package for eligible roles may include base salary, equity, and benefits. Typical benefits include health, dental, vision, retirement options, learning stipend, and generous PTO. Specific eligibility and package details will be discussed during the hiring process.
How We Work / Team Values
Our client values customer-centered engineering, cross-team collaboration, and quality as a competitive advantage. Expect to work in small, outcome-driven teams that prioritize shipping, measurement, and long-term impact.
Location & Eligibility
- Job location: San Francisco, California, USA.
- Candidates should be eligible to work for the Confidential Client in the U.S.; specific hiring and relocation support will be discussed during recruiting.
Notes & Process
- The Confidential Client may require a waiting period before reconsidering candidates for the same role (policy details will be shared by the recruiter if applicable).
- Reasonable accommodations are available for applicants with disabilities—please request accommodations through the recruiting process.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
- If you have questions about how your data is used, please contact us directly.