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Strategic Project Lead - Code

Training Superintelligence· Frontier Data Operations
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Hybrid (Remote (India))full-timePosted 1mo ago

About the role

Lead the production system behind Turing’s software-engineering data programs, turning complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost. Manage large-scale, distributed engineering programs including supervised coding demonstrations, RL environments, benchmarks, and rubric-based evaluations while coordinating hundreds of contributors and maintaining world-class data integrity.

Responsibilities

  • 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.
  • 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.
  • 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.
  • 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 long-term trust that converts projects into multi-year partnerships and identify expansion opportunities.
  • 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.

Qualifications

  • Background in software engineering, technical program management, consulting, finance, startups, or other operationally intense environments with a track record of managing complex, multi-stakeholder projects.
  • Strong analytical and communication abilities; ability to spot bottlenecks, build measurement plans, and communicate fixes clearly.
  • Customer-facing experience: comfortable working directly with high-profile clients, managing expectations, and building long-term relationships.
  • Excited by process optimization and large-scale execution; thrives on making operations faster, cleaner, and more reliable.
  • Ability to read and review code and follow PRs in Python, TypeScript, Java, or Go; read test suites and judge delivered tasks 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 frontier lab.

Skills

Required:Program managementCode literacyData quality and analytics

Benefits

  • Competitive compensation package
  • Opportunities to publish and participate in top AI conferences
  • High ownership and visibility with senior leadership
  • Direct collaboration with leading AI labs and researchers
  • Engaging, mission-driven work at the frontier of AI research and deployment
  • Inclusive, diverse, and authentic workplace environment
Last updated Sep 2, 2026. Interested? Apply on the company site.

About Training Superintelligence

Turing develops large-scale RL environments and data generation systems that train multimodal agents to improve model performance in coding, real-world, economically valuable tasks, and advanced STEM reasoning.

Train AIBuild AIHire AI TalentAI for BFSIEMNAIDatasetsEnterprise Knowledge WorkMultimodal
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