Jobs at Mercor

The Strategic Project Lead will drive execution of multi-million-dollar projects, optimize processes, and manage a large team while maintaining client relationships.

Conduct research on post-training, reinforcement learning with verifiable rewards, data generation, and language model evaluation. Design controlled experiments, develop benchmarks and scoring frameworks, analyze model failures, build research tooling and data pipelines, and communicate findings through reports and presentations. Collaborate with research scientists, engineers, AI teams, and domain experts, contributing to publications, benchmark releases, and frontier AI systems.

Own the architecture and implementation of Applied AI backend systems, including APIs, data models, distributed pipelines, orchestration, infrastructure, and production reliability. Lead technical direction, build high-throughput services, manage containerized infrastructure with Terraform, participate in on-call, resolve incidents, mentor senior engineers, and collaborate across product, operations, and research teams. The role requires strong backend, database, distributed systems, and production operations expertise, plus enthusiasm for agentic AI development.

Build and operate backend services for Mercor’s Applied AI platform, including APIs, data models, background jobs, and high-throughput pipelines. Own features from design through production, with responsibility for reliability, observability, performance, infrastructure, containerized environments, and incident response. Collaborate with product, operations, and research teams to turn ambiguous requirements into production systems.

Build and lead Mercor’s finance-sector client function from the ground up. Identify, onboard, and manage financial services clients; own relationships from scoping through renewal and expansion; negotiate pricing, contracts, compliance, and data-rights terms; and coordinate internal Product, Research, Operations, Legal, and Finance teams. Develop repeatable service playbooks and processes while independently driving outreach, documentation, stakeholder management, and deal closure.

Build end-to-end sensor data pipelines that ingest multi-sensor captures (video, depth, inertial, audio), perform segmentation, pre-labeling, automated QC, privacy redaction, encoding and packaging, and deliver validated, versioned datasets at petabyte scale for frontier AI labs.

Mercor is offering $5 million in grants for research on AI capabilities, including real-world evaluations, interactive environments, long-horizon tasks, agentic systems, reasoning, post-training, and evaluation methodology. Academic groups, independent researchers, and nonprofits may apply with a focused proposal. Applicants should describe their team, background, research accomplishments, project, expected outputs, impact, timeline, and resource needs. Funded projects are expected to produce public research, datasets, methodologies, or tools.

Develop and implement frontier-model post-training methods, including reinforcement learning, verifiable rewards, evaluation, and data-centric optimization. Design rigorous experiments across datasets, rewards, environments, and training strategies; investigate model behavior and failure modes; build scalable data-generation and evaluation pipelines; and create benchmarks, rubrics, and scoring systems. Collaborate with researchers, engineers, AI teams, customers, and domain experts while contributing to open-source tools, technical reports, blog posts, and research papers.

Lead high-priority go-to-market initiatives across sales, partnerships, marketing, and recruiting. Develop sales strategy, activate strategic partnerships, incubate product, events, and customer marketing programs, identify organizational needs, lead strategic hiring, and own special projects from strategy through execution. The role requires strong commercial judgment, exceptional communication, high ownership, and comfort operating in an ambiguous, rapidly scaling AI company.

Build and ship production backend systems supporting talent platforms and applied AI data workflows. Interns own projects end-to-end, collaborate with product, design, researchers, and AI companies, and develop scalable systems that impact customers. Responsibilities include writing production-grade code, designing systems, working with APIs and databases, and contributing to AI-focused products in a fast-paced, in-person environment.

Analyze data affecting ranking, hiring efficiency, candidate experience, and revenue. Design experiments, build dashboards and data models, improve data quality, prototype matching and scoring models, and evaluate LLM-powered systems through rubrics and human-in-the-loop studies. Collaborate with engineering, product, and leadership to translate rigorous analysis into product decisions.

Mercor is offering $5 million in grants for independent researchers, academics, PhD students, and small teams conducting frontier AI safety research. Focus areas include misalignment, sandbox escape, evaluation awareness, interpretability, oversight and control, and red-teaming. Funding may support researcher time, API credits, and conference attendance. Applicants should submit a focused expression of interest describing their team, background, research proposal, outputs, impact, timelines, and resource needs.

Own core product journeys from initial flows through polished UI, collaborate with product and engineering, simplify complex experiences, evolve Mercor’s visual language, shape design culture, and improve product tutorials. The role requires strong UX and visual design skills, autonomy, and close attention to implementation constraints, with bonus experience in AI products or marketplaces.

Own recruiting operations for engineering hiring, including scheduling, ATS management, interview-loop coordination, funnel analytics, process improvement, candidate experience, and onboarding logistics. Partner with technical recruiters, hiring managers, interviewers, and leadership to manage requisitions, identify bottlenecks, improve workflows, maintain dashboards, and support high-velocity hiring.

Own Mercor’s data platform infrastructure across Snowflake, Fivetran, Airflow, Astronomer, and Hex. Responsibilities include data organization, role-based access control, row-level security, PII masking, governed migrations, pipeline reliability, on-call support, dashboard governance, warehouse cost optimization, and CDC or streaming ingestion. The role also establishes platform standards and builds internal tooling for a new Data Platform team.

Own complex AI and data projects from customer discussions through delivery, translating needs into execution plans and coordinating large networks of domain experts. Lead and develop project associates, manage customer relationships, analyze performance data, improve quality and efficiency, and identify expansion opportunities. Collaborate with Operations, Engineering, and Machine Learning teams while overseeing projects with substantial revenue and contributor scale.

Execute large-scale projects for AI labs and technology companies, managing expert networks, multimillion-dollar portfolios, delivery quality, operational issues, customer communication, and process improvements. The role requires analytical problem-solving, prioritization, ownership, and comfort with ambiguity while collaborating across operations, engineering, and machine learning teams. Candidates may be recent graduates and will work remotely from Mexico City before transitioning to an in-person model.

Own Mercor’s security GRC and compliance programs, including continuous SOC 2 monitoring, ISO 27001 certification, customer audits, third-party risk, policy lifecycle management, controls-as-code, data-handling procedures, and enterprise security questionnaires. Build the company’s first GRC function, automate evidence collection and questionnaire responses, manage auditor and customer relationships, and support frameworks such as HIPAA, FedRAMP, and EU AI Act conformity.

Lead the technical strategy and development of multimodal data products spanning image, video, audio, documents, processing, review, validation, versioning, and delivery. Design reliable, traceable, cost-efficient distributed systems, remain hands-on with production code, and manage engineering staff through hiring, coaching, delegation, and performance development. Partner with product, ML, operations, and customer teams to build reusable capabilities and operate complex workflows at scale.

As an Infrastructure Engineer, you'll design and maintain cloud infrastructure, build automation workflows, manage CI/CD pipelines, and improve system reliability while collaborating with product and research teams.