Software Engineer, Applied AI
AI summary of the role
This is a high-ownership, deeply technical software engineering role at a $10B AI data company, building and operating systems that sit between frontier AI research and data delivery.
What you’ll do
- 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
What you’ll bring
- 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
Technologies
Python · Go · Rust · model training · inference · statistical analysis · experimental design · LLM evaluation · data pipelines · synthetic data generation
About Mercor
Marketplace matching domain experts (doctors, lawyers, scientists, engineers) with AI labs to generate post-training data, evaluations, and reinforcement learning signal.
Series C
Source and classification
Production engineering · Evidence for this classification:
valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role 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. What You’ll Do Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs Build and operate scalable data
More from the job description
About Mercor 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. About the Role 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 projec [... source excerpt omitted ...] 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 What Makes This Role Different 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 communicat [... source excerpt omitted ...] vements Familiarity with evaluation methods for large language models Comfort working through ambiguity and shipping iteratively You’re likely someone who 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 Why Engineers Join 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. Benefits Bi-annual performance bonu
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