Jobs at Turing

Lead and grow an engineering team, owning delivery, health, and career development. Hire and retain engineers, set engineering standards, provide technical direction, partner cross-functionally, and own operational excellence including incidents and on-call.

Lead end-to-end GenAI projects for enterprise clients: manage client relationships, select use-cases, provide technical direction, coordinate cross-functional teams, oversee delivery planning and execution, ensure documentation and ROI, and mitigate risks to scale POCs into production.

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.

Lead end-to-end design, build, and production operation of scalable distributed systems. Debug production issues, improve reliability and performance, conduct code reviews, mentor junior engineers, and collaborate cross-functionally to deliver high-quality software at scale with an AI-forward mindset.

Set technical direction across multiple services and teams; lead cross-cutting initiatives like migrations and modernization; own reliability and performance at scale; raise engineering standards through design docs and reviews; mentor senior engineers and partner with leadership on technical roadmaps.

The Strategic Project Lead manages strategic data delivery projects for AI labs, overseeing project execution, customer relationships, and contributor coordination to ensure high-quality outcomes and maintain long-term partnerships.

Lead discovery with stakeholders to map workflows and controls, write clear problem statements and delivery-ready requirements (user stories, acceptance criteria), partner with product and engineering, support UAT and testing, maintain traceability and auditability, and use AI tools responsibly to accelerate analysis and documentation.

Lead discovery and delivery of AI-enabled back-office finance solutions. Define roadmap, translate workflows into epics/stories, coordinate engineering and data science, manage stakeholders, prioritize backlog, ensure controls, and run disciplined execution for reconciliation, NAV, GL, and operational controls.

The AI Engineering Lead at Turing will lead a team to deliver Generative AI solutions, building technical roadmaps, designing architectures, and ensuring execution to meet client needs.

Lead end-to-end multimodal AI programs as the primary client-facing delivery owner. Design scalable annotation, evaluation, and RLHF pipelines across vision, image/video generation, and audio; define quality systems and rubrics; build and manage cross-functional delivery teams; translate model requirements into program plans; track milestones, risks, and metrics; and drive account growth and operational playbooks for US clients while working LATAM hours.

The Research Engineer role involves building and improving deep learning systems, focusing on data quality, dataset and RL environment design, and collaborating with researchers to meet high standards for AI applications.

The Research Engineer will design datasets and RL environments, ensuring high data quality for AI systems development, and collaborate with teams to evaluate outcomes.

As a Software Engineering evaluator, you will curate code examples and evaluate AI-generated code for efficiency while collaborating with cross-functional teams to enhance AI-driven solutions.

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.

The role involves leading the engineering team in developing and deploying Generative AI applications, managing the technical roadmap, and collaborating with cross-functional teams to deliver AI solutions.

As a Senior AI Solutions Engineer, you will lead technical conversations with AI research partners, translate their needs into solutions, manage proof of concepts, and construct a playbook for future engineers.

The Forward Deployed Engineer will design, build, and deploy GenAI applications for customers, collaborating with various teams and ensuring robust solutions using Python and cloud platforms.

The Senior AI Solutions Engineer will lead technical discovery, build solutions, own pilot projects, and create a playbook for the enterprise knowledge work domain. Responsibilities include engaging with research partners, designing evaluations, and translating goals into deliverables while ensuring successful prototype demonstrations before contract signing.

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.