トレンド企業

Mercor
Mercor

Software Engineer, Fullstack

職種フルスタック
経験ミドル級
勤務地San Francisco, Canada, United States
勤務オンサイト
雇用正社員
掲載2ヶ月前
応募する

必須スキル

Python

React

SQL

Go

MongoDB

Next.js

ABOUT MERCOR

Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.

Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our new San Francisco headquarters.

About the Role:

We're looking for a product-oriented full-stack engineer with strong technical fundamentals and exceptional product taste. This role is ideal for someone who enjoys owning user-facing features end-to-end—from idea to production—while deeply understanding the business and marketplace dynamics behind what they're building.

You'll work on core marketplace surfaces that impact how engineers discover Mercor, apply to opportunities, complete assessments, and ultimately earn income. Success in this role requires good judgment, comfort operating in ambiguity, and the ability to ship high-quality experiences quickly without over-engineering.

This is not a narrowly scoped backend or frontend role. You'll regularly work across:

Frontend: React / Next.js, user flows, UX details, performance, and polish

Backend: Python and Go services, APIs, data models, and integrations

Data: MongoDB and SQL, metrics, funnel analysis, and operational correctness

At the end of the process, you’ll be team-matched to where you can have the most impact, on one of the following:

  • Talent platform side – building next-generation tools that automate recruiting end-to-end, intelligently match candidates to roles, and power global hiring with seamless contracts and payments.

  • Applied AI/human data side – partnering with top AI researchers from the AI labs like OpenAI, Anthropic, and Google to create post training datasets to improve foundational model capabilities.

What You’ll Do:

  • Own product features end-to-end, from scoping and design partnership to implementation, launch, and iteration

  • Build and maintain frontend experiences in React / Next.js with strong UX judgment and attention to detail

  • Design and implement backend APIs and services in Python and Go that power marketplace workflows

  • Model and evolve data using MongoDB and SQL, balancing correctness, flexibility, and performance

  • Partner closely with Product and Design to make trade-offs between speed, quality, and long-term maintainability

  • Develop intuition for marketplace dynamics (supply, demand, incentives, trust, activation, drop-off) and reflect that in product decisions

  • Instrument features, analyze funnels, and iterate based on real user behavior

  • Raise the bar for code quality, system design, and product craftsmanship through reviews and collaboration

What We’re Looking For:

  • Product & Taste

  • Strong product intuition and UX sensibility—you care deeply about how things feel, not just whether they work

  • Ability to reason about user behavior, incentives, and marketplace dynamics

  • Comfort making product decisions when requirements are incomplete or evolving

  • Technical

  • Experience building full-stack web applications in production

  • Strong frontend experience with React / Next.js

  • Backend experience with Python and/or Go, including API design and service ownership

  • Familiarity with MongoDB and relational databases (SQL) and when to use each

  • Track record of shipping features end-to-end in fast-moving environments

  • Execution & Ownership

  • Bias toward action and ownership—you take responsibility for outcomes, not just tasks

  • Ability to balance speed with long-term quality and know when "good enough" is correct

  • Clear communicator who can align technical decisions with business goals

  • Nice to Have

  • Experience working on marketplaces, consumer products, or growth-oriented platforms

  • Strong intuition for onboarding, activation, and funnel optimization

  • Experience working closely with designers and PMs in highly iterative product cycles

Why Mercor

  • Impact: Your work powers how the world’s leading AI labs train and test their models.

  • Learning: Get early insights into frontier model capabilities months before the market.

  • Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.

Benefits:

  • Generous equity grant vested over 4 years

  • A $20K relocation bonus (if moving to the Bay Area)

  • A $10K housing bonus (if you live within 0.5 miles of our office)

  • A $1K monthly stipend for meals

  • Free Equinox membership

  • Health insurance

閲覧数

0

応募クリック

0

Mock Apply

0

スクラップ

0

Mercorについて

Mercor

Mercor

Seed

Mercor is an AI-powered platform that connects companies with vetted software engineers and technical talent through automated screening and matching processes.

1-50

従業員数

San Francisco

本社所在地

レビュー

10件のレビュー

4.0

10件のレビュー

ワークライフバランス

3.2

報酬

3.8

企業文化

4.3

キャリア

3.5

経営陣

4.2

72%

知人への推奨率

良い点

Supportive and approachable management

Great team culture and collaborative environment

Good benefits and flexible work options

改善点

Heavy workload and frequent overtime

Communication issues and miscommunication

Non-competitive pay and limited career progression

給与レンジ

6件のデータ

Mid/L4

Mid/L4 · Machine Learning Engineer

1件のレポート

$210,126

年収総額

基本給

$161,637

ストック

-

ボーナス

-

$210,126

$210,126

面接レビュー

レビュー3件

難易度

3.0

/ 5

内定率

67%

体験

ポジティブ 0%

普通 67%

ネガティブ 33%

面接プロセス

1

Application Review

2

AI Interview Screen

3

Technical Assessment

4

Final Review

5

Offer

よくある質問

Domain Expertise

Behavioral/STAR

Industry Knowledge

Leadership Experience

Problem Solving