Jobs at Turing

The Senior Technical Recruiter will source, engage, and close elite research engineering and AI talent. Responsibilities include mapping passive talent across academia, research labs, startups, GitHub, arXiv, and OpenReview; building proactive pipelines; assessing technical relevance; partnering with research and executive leaders; and developing customized closing strategies for highly contested offers. The role requires deep technical recruiting experience, AI/ML domain literacy, compensation and equity knowledge, startup speed, and strong ownership.

Build and operate reliable, secure, and scalable cloud infrastructure across GCP, AWS, and Azure. Develop developer platforms, CI/CD pipelines, Terraform infrastructure-as-code, deployment automation, and production Kubernetes environments. Respond to incidents, perform root-cause analysis, improve monitoring and cloud efficiency, secure networking and infrastructure, and mentor engineers. Participate in a global on-call rotation while partnering with application and security teams.

Own end-to-end delivery of software-engineering data programs, including scope, timelines, quality, throughput, cost, contributor performance, and customer reporting. Coordinate hundreds of distributed engineers, optimize annotation and evaluation workflows, analyze quality data, build automation and reusable playbooks, and serve as the primary client contact for AI research organizations. The role requires technical fluency sufficient to inspect code, tests, workflows, and evaluation results while leading large-scale operational execution.

Lead product marketing for Turing’s Frontier AI business by developing positioning, messaging, launch plans, technical content, customer research, competitive intelligence, and sales enablement. Partner with AI researchers, Sales, and Customer Success to translate complex AI capabilities into compelling value propositions, support product adoption, and inform roadmap decisions through customer and market insights.

Own the vision, roadmap, prioritization, and delivery of back-office operations and controls platforms supporting fund accounting and global finance. Partner with controllers, finance, operations, engineering, and technology teams to modernize workflows, reporting, automation, and governance. Translate fund control requirements into product specifications, user stories, and acceptance criteria while managing dependencies, risks, milestones, and stakeholder communication. Identify practical AI opportunities to improve operational efficiency.

Own the end-to-end development and delivery of reinforcement learning environments for frontier AI labs and enterprise clients. Lead environment design, task generation, reward and verifier development, data quality, evaluation, and post-training experiments. Build and manage cross-functional engineering, research, domain expert, QA, and data operations teams. Establish technical processes, schemas, APIs, validation scripts, and review systems while managing customer relationships, solutioning, delivery, and project growth.

Owns end-to-end development of datasets, reinforcement learning environments, and evaluations for coding agents and software engineering models. Leads engineers, researchers, QA professionals, and data creators; establishes quality processes, pipelines, validation, and review workflows. Collaborates directly with frontier AI labs, fine-tunes models, builds benchmarks, develops automation and internal tools, and supports customer-facing enablement. The role combines hands-on technical leadership, engineering management, operational execution, research, and industry thought leadership.

The Client Director will lead large-scale LLM training programs, managing global teams, ensuring data quality, and overseeing client relationships. Responsibilities include optimizing workflows, developing automation tools, and enhancing model performance through high-quality datasets.

Develop and optimize LLM-based solutions, maintain code in Python and SQL, integrate with cloud services, and provide mentoring. Collaborate cross-functionally and innovate in generative AI techniques.

The Staff Research Engineer - Code will lead the creation of datasets and reinforcement learning environments for coding agents, collaborating with AI labs to influence model improvements and operational excellence, while managing a technical team.

This role involves building and deploying AI/ML models, leading engineering teams, ensuring timely execution of projects, and continuously innovating in generative AI and LLM applications.

Lead and optimize Talent Operations processes at scale, manage KPIs and a 15+ person team, drive AI-forward automation, improve candidate experience, own stakeholder reporting, and execute cost and process optimization initiatives.

Own community strategy and execution for developer (supply) and customer (demand) audiences. Manage social channels, virtual and in-person events, partnerships, ambassador programs, and cross-functional alignment. Track community KPIs and deliver monthly performance briefings to drive engagement, retention, and top-of-funnel impact.

Own the People Team’s HRIS, ATS, data governance, workflows, KPIs, dashboards, and automation roadmap. Lead a team of three while integrating Recruiting and People Operations across sourcing, hiring, onboarding, employee lifecycle management, and offboarding. Establish policies, SLAs, documentation, operational controls, and continuous improvement practices. Partner with engineering, AI, IT, Finance, Legal, and HR stakeholders to resolve system issues, prioritize integrations, improve data quality, and reduce manual work.

Provide high-trust executive and personal support to the Founder & CEO: manage a complex, rapidly changing calendar; coordinate domestic and international multi-leg travel; handle personal, household, and family-office logistics; anticipate needs, solve problems proactively, and maintain confidential systems for files, contacts, and expenses. Partner closely with the Office of the CEO and internal/external stakeholders to preserve the CEO's time and priorities.

Lead end-to-end delivery of software-engineering data programs for frontier AI labs: design and run data pipelines, coordinate 100–1,000+ contributors, ensure annotation and dataset quality, manage client relationships, diagnose bottlenecks, and codify scalable operational playbooks.

Support the CEO as an external force multiplier: run capital formation processes, craft investor/partner decks and memos, drive strategic partnerships with frontier labs and enterprises, build executive relationship systems, and lead high-impact confidential projects requiring judgment, discretion, and flawless execution.

Lead design, development, fine-tuning, and deployment of LLM-based GenAI solutions (RAG, agents, prompt engineering). Own technical roadmaps, drive engineering delivery, mentor teams, integrate cloud deployments (Azure/GCP/AWS), maintain Python/SQL codebases (LangChain/LangGraph), and collaborate with product, data science, and business stakeholders.

The Forward Deployed AI Engineer designs, builds, and deploys intelligent applications using Python and related technologies, addressing customer needs and leading deployment projects.

Support strategic initiatives through research, analysis, and execution. Collaborate cross-functionally with GTM, product, engineering, and data science. Perform data analysis, track metrics, create project plans, monitor milestones, improve processes, and prepare reports, presentations, and dashboards for leadership.