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求人Handshake

Associate Software Engineer, RLE

Handshake

Associate Software Engineer, RLE

Handshake

San Francisco, CA

·

On-site

·

Full-time

·

Today

About Handshake

Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.

Why join Handshake now:

  • Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

  • Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions

  • Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others

  • Build a massive, fast-growing business with billions in revenue

About the Role

We’re hiring an Associate Software Engineer to help build our Reinforcement Learning Environments (RLE) platform—the systems where frontier AI models learn to complete real-world work.

This is a hands-on, growth-oriented role where you’ll contribute to building core systems, learn quickly from senior engineers, and gain exposure to cutting-edge AI infrastructure.

Location:

San Francisco, CA (in-office, 5 days/week)

What You’ll Do

  • Contribute to building RLE environments and supporting infrastructure

  • Implement features across backend systems and frontend interfaces

  • Work with senior engineers to improve system reliability and performance

  • Help build modular workflow domains (e.g., engineering, finance, legal)

  • Support data pipelines that power model training and evaluation

What We’re Looking For

  • 0–2 years of experience (internships or full-time) in software engineering

  • Familiarity with backend development and APIs

  • Working knowledge of React

JS and TypeScript:

  • Understanding of databases (e.g., PostgreSQL) and basic system design

  • Eagerness to learn and operate in fast-paced environments

Nice to Have

  • Exposure to cloud platforms (AWS, GCP)

  • Experience with data pipelines or ML-adjacent systems

  • Interest in AI/ML or simulation systems

What Success Looks Like

  • Ships reliable features that improve RLE functionality

  • Grows into owning small components independently

  • Contributes to faster iteration and better developer velocity

Perks

Handshake delivers benefits that help you feel supported—and thrive at work and in life.

The below benefits are for full-time US employees.

🎯 Ownership: Equity in a fast-growing company

💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching

🍼 Family Support: Paid parental leave, fertility benefits, parental coachin

💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend

📚 Growth: $2,000 learning stipend, ongoing development

💻 Office: Commuting support, free lunch, and gym in our SF office

🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days

🤝 Connection: Team outings & referral bonuses

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Handshakeについて

Handshake

Handshake

Series E

Handshake is a career services platform that connects college students and recent graduates with employers for job opportunities and recruiting.

501-1,000

従業員数

San Francisco

本社所在地

$3.5B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

3.7

報酬

2.8

企業文化

4.1

キャリア

2.5

経営陣

3.2

72%

友人に勧める

良い点

Flexible work arrangements and remote options

Supportive team and environment

Good leadership and vision

改善点

Limited growth and promotion opportunities

Compensation could be better

Management needs improvement

給与レンジ

7件のデータ

Mid/L4

Senior/L5

Staff/L6

Mid/L4 · Data Scientist

0件のレポート

$167,500

年収総額

基本給

-

ストック

-

ボーナス

-

$142,375

$192,625

面接体験

5件の面接

難易度

3.2

/ 5

期間

14-28週間

内定率

60%

体験

ポジティブ 60%

普通 0%

ネガティブ 40%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Final Interview

6

Offer

よくある質問

Technical Knowledge

Behavioral/STAR

Coding/Algorithm

Past Experience

Culture Fit