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Software Engineer, Applied AI
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Mercor·New York City·27 авг.

Software Engineer, Applied AI

🏢 ОфисMiddleПолная занятость
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Наша компания

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. 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 San Francisco, NYC, or London offices.

Чем предстоит заниматься

As a Software Engineer on Applied AI, you’ll build, deploy, and operate systems that sit directly between frontier AI research and data delivery
This is a high-ownership, deeply technical role. You’ll work through ill-defined problems, prototype quickly with researchers and customers, and take systems from early experiments to reliable, scalable production. You’ll own projects end-to-end: spanning requirements gathering, creating data creation pipelines, and improving model-adjacent infrastructure, while partnering closely with frontier AI labs and Mercor’s internal teams to ship high-impact applied AI solutions
Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs
Build and operate scalable data pipelines for post-training workflows and model evaluations
Design and build scalable systems for synthetic data generation and data quality, and work directly with customers to understand requirements and develop technical solutions
Prototype new data types, benchmarks, and evaluation frameworks
Lead technical discussions with customers

Наши требования

Strong backend engineering fundamentals in a modern language (Python, Go, Rust, etc.)
Experience with model training and inference
Strong grounding in statistical analysis and experimental design for measuring model performance and improvements
Familiarity with evaluation methods for large language models
Comfort working through ambiguity and shipping iteratively

Мы предлагаем

Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k Relocation bonus
$10K proximity bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance

Дополнительно

Direct frontier exposure. You’ll work closely with researchers at leading AI labs, building infrastructure that directly accelerates cutting-edge research
Coding + customer work. This role blends deep technical execution with customer interaction. Engineers who enjoy both building and communicating tend to thrive
Fast-moving, high-ownership environment
Technically demanding, collaborative work
“Building the plane while flying it”
In-person culture at our new New York office at One World Trade Center
Aligned with frontier research timelines
Enjoys ownership and customer-facing problem solving
Thinks entrepreneurially and moves quickly
Balances speed with engineering rigor
Communicates clearly with technical and non-technical users
Direct exposure to frontier AI research
Real ownership and visible impact
Technical depth paired with human interaction
Fast feedback loops and high leverage
There are very few roles that combine this level of technical rigor, customer proximity, and research exposure
M
Mercor
New York City

ГрейдMiddle
ЗанятостьПолная занятость
РегионНе Россия
ФорматОфис
ИсточникСкрыто
Опубликовано27 авг.
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