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トレンド企業

トレンド企業

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求人Handshake

Software Engineer I, RLE

Handshake

Software Engineer I, RLE

Handshake

San Francisco, CA

·

On-site

·

Full-time

·

1d ago

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 a Software Engineer to build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work.

This role owns meaningful components end-to-end and plays a key part in scaling systems that power model training and evaluation.

Location:

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

What You’ll Do

  • Build and scale core components of RLE environments and infrastructure

  • Design and implement backend systems and data pipelines

  • Translate ambiguous product and research needs into production systems

  • Develop modular, reusable workflow domains

  • Improve reliability, observability, and system performance

What We’re Looking For

  • 2–4 years of experience in backend, distributed systems, or ML-adjacent infrastructure

  • Strong proficiency in React

JS and TypeScript:

  • Solid experience with relational databases (PostgreSQL) and data modeling

  • Experience with cloud infrastructure (AWS/GCP) and CI/CD

  • Ability to independently drive projects from design to production

Nice to Have

  • Experience with simulation systems or evaluation platforms

  • Exposure to ML systems or working with research teams

  • Experience in fast-moving, operations-heavy environments

What Success Looks Like

  • Owns and delivers key RLE components end-to-end

  • Improves system scalability and developer velocity

  • Enables faster launch of new domains with high-quality data

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 coaching

💝 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