Strategic Project Lead Code

Based in San Francisco California Turing is the worlds leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data specialized talent and training pipelines that advance thinking reasoning coding multimodality and STEM. For enterprises Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows unlock transformative outcomes and drive lasting competitive advantage.

Recognized by Forbes The Information and Fast Company among the worlds top innovators Turings leadership team includes AI technologists from Meta Google Microsoft Apple Amazon McKinsey Bain Stanford Caltech and MIT. Learn more at

You will own the production system behind Turings software-engineering data programs turning complex research requirements into predictable delivery across quality throughput contributor performance timelines and cost.

These programs may involve supervised coding demonstrations repository-level tasks agentic trajectories reinforcement-learning environments benchmarks code review and rubric-based evaluations. They can require coordinating hundreds of distributed software engineers while responding quickly to changing research requirements.

This is an operations leadership role with a meaningful technical bar. You must be able to inspect code understand tests interrogate quality signals and challenge a workflow or rubric when it is not producing the intended result. You will not be expected to act as the principal engineer for every program. Your primary responsibility is to build and operate the system that consistently produces high-quality technical work at scale.

1) Operational execution own end-to-end delivery on every project you run

• Design and manage data pipelines from customer specification to final delivery with full accountability for scope timeline and quality.
• Scope and stand up coding workstreams across supervised demonstrations agentic trajectories RL environments benchmark construction and rubric-graded evaluation.
• Diagnose bottlenecks in real time re-sequence workflows refine instructions create incentive systems and scale review processes to hit throughput targets.

2) Quality ownership ensure world-class data integrity on every project

• Own quality control across the annotation lifecycle: set the bar measure against it and close the gap when it slips.
• Analyze datasets to identify trends anomalies and systematic errors then fix the root cause not just the symptom.
• Implement and continuously improve annotation evaluation and curation best practices.

3) Large-scale coordination orchestrate the work ofcontributors

• Define the required contributor profile and partner with talent teams to source assess onboard and ramp distributed software engineers.
• Own contributor training performance management reviewer capacity incentives and corrective actions.
• Build team-lead and reviewer structures that maintain execution standards across programs involving hundreds of contributors.

4) Customer relationships be the face of Turing to the worlds leading AI labs

• Act as the primary point of contact for researchers and program managers at frontier AI labs providing clear reporting on progress quality risks and recovery actions.
• Translate research intent into a task specification and push back when a spec will not produce the signal the researcher actually wants.
• Build the kind of long-term trust that converts a one-off project into a multi-year partnership and identify expansion opportunities along the way.

5) Playbook building codify what works so future SPLs scale faster than you did

• Use Python SQL or other appropriate tools to automate quality sampling defect classification throughput analysis and weekly reporting.
• Turn successful workflows into reusable playbooks quality controls evaluation assets and contributor-management systems.
• Share lessons and mentor other SPLs so each program improves the operating system for the next one.

• Background in software engineering technical program management consulting finance startups or other operationally intense environments with a proven track record of managing complex multi-stakeholder projects.
• Strong analytical and communication abilities: you can spot a bottleneck in a noisy production environment build a measurement plan and communicate the fix to a demanding client in plain language.
• Customer-facing experience: comfortable working directly with high-profile clients managing expectations and building long-term relationships.
• Excited by gritty process optimization and large-scale execution you thrive on making complex operations faster cleaner and more reliable.
• You can read and review code. You can follow a pull request in Python TypeScript Java or Go read a test suite and judge a delivered task independently.
• Bonus: Experience with agentic evaluation harnesses software engineering benchmarks or RL environments; Experience managing large distributed contributor networks or marketplaces; Prior work at an AI data vendor or a frontier lab

30 days: Complete technical and operational calibration establish the program baseline validate acceptance criteria and delivery controls and independently lead a defined workstream.

90 days: Deliver predictable throughput and quality improve at least one material operating metric maintain a trusted risk and reporting cadence and demonstrate that defects are being detected internally before customer delivery.

180 days: Run concurrent programs with stable quality and cost performance convert successful workflows into reusable assets contribute evidence that supports account expansion and help another lead or team adopt the operating system you built.

• Work directly with the worlds leading AI labs at the cutting edge of post-training evaluation and agentic AI research.
• Real impact on the path to AGI: the data you deliver will directly influence how frontier models are trained and evaluated.
• High ownership and influence. You will shape how Turing delivers at scale with direct visibility to senior leadership.
• Direct-to-research customers. You will spend your time partnering with the people building the future of AI not coordinating with procurement.

• We are client first: We put our clients at the center of everything we do because their success is the ultimate measure of our value.

• We work at Start-Up Speed: We move fast stay agile and favor action because momentum is the foundation of perfection

• We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.