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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.
Job Responsibility:
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
Requirements:
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