Team Lead - Coding Data Annotation (LLM Training)

About Turing

Based in San Francisco, California, Turing is the world’s 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 world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com

 

 

 

Location: Remote
Experience Level: 5–12+ years (hands-on required)
Functional Area: Engineering Leadership / LLM Data Quality
Role Type: Full-time

About the Role

We are looking for a hands-on Team Lead / Engineering Manager to lead high-quality coding data annotation workstreams that support training and evaluation of Large Language Models (LLMs). This role sits at the intersection of software engineering, workflow automation, and data quality, requiring someone who can lead developers while still contributing technically.

You will architect workflows, guide coding annotators, design validation pipelines, ensure quality bar consistency, and collaborate closely with Delivery Managers and Product Managers on project execution. This is not a pure management role — deep technical expertise and hands-on coding ability are essential.

Key Responsibilities

Technical Leadership

• Architect and maintain high-quality workflow systems for coding data generation and validation.
  
  
• Design coding automations, execution environments, and quality gates to ensure correctness of produced data.
  
  
• Review team outputs for code correctness, clarity, robustness, and quality standards.
  
  
• Build scalable solutions for tasks such as:
  
  
• RLHF data pipelines
  
  
• SFT datasets
  
  
• Competitive-programming–style annotation
  
  
• Model-breaking tasks, benchmarks, verifiers
  
  
• GYM systems (UI and non-UI)
  
  
• Provide hands-on engineering support across Python, JavaScript, or domain-specific languages.
  
  

Team Leadership & Management

• Lead a team of developers/annotators to deliver high-quality results for specific coding workstreams.
  
  
• Provide coaching, technical mentorship, and best practices for code quality.
  
  
• Collaborate with Delivery Managers and PMs on project planning, annotation guidelines, KPI tracking, and quality frameworks.
  
  
• Support hiring and onboarding of engineers and annotators.
  
  

Cross-Functional Collaboration

• Work with AI research, engineering, data, and tooling teams to align workflows with model requirements.
  
  
• Interface with infrastructure teams for deployment, execution pipelines, and testing environments.
  
  
• Communicate quality risks, improvements, and blockers effectively.
  
  

Required Qualifications

Technical Experience

• 5+ years of hands-on coding experience for standard annotation projects.
  
  
• 7+ years preferred for complex SFT, verifier, benchmark, or system-heavy workflows.
  
  
• Strong proficiency in Python; familiarity with JavaScript/TypeScript is highly desirable.
  
  
• Experience with one or more of the following (depending on project):
  
  
• Competitive programming problems
  
  
• Debugging and analyzing multi-language code
  
  
• Pipeline design and automation
  
  
• Backend services, databases, and tooling for non-UI GYMs
  
  
• Frontend/UI systems (React/Next.js) for UI GYMs
  
  
• Ability to architect and deploy end-to-end systems.
  
  

Leadership Experience

• Has led engineering or development teams with responsibility for code quality and technical direction.
  
  
• Demonstrated ability to remain hands-on even in leadership roles.
  
  
• Strong background in reviewing code, maintaining standards, and improving engineering workflows.
  
  

AI Mindset

• AI/ML experience is a plus, but not mandatory.
  
  
• Must be:
  
  
• AI-forward
  
  
• Able to grasp LLM concepts quickly
  
  
• Comfortable learning domain-specific processes
  
  
• Personal AI projects or experimentation are a strong positive signal.
  
  

Nice-to-Have Skills

• Experience with LLM training workflows (RLHF, SFT, reward modeling, evaluators).
  
  
• Familiarity with dataset creation, quality scoring, or model verifiers.
  
  
• Contributions to open-source tools or AI-related projects.
  
  
• Experience building annotation tools, internal developer platforms, or automation systems.
  
  

Who Thrives in This Role

• Hands-on leaders who enjoy both coding and coaching.
  
  
• Engineers who care deeply about code correctness, quality, and reproducibility.
  
  
• People who enjoy solving ambiguous technical problems in emerging AI workflows.
  
  
• Builders who want to contribute directly to how LLMs are trained and evaluated.
  
  

Who Is Not a Fit

• Pure program managers or non-technical managers.
  
  
• Senior leaders who no longer write or review code.
  
  
• Engineers unable to adapt across languages or unfamiliar with quality-first coding.
  
  

Interview Expectations

• Technical screening including coding and system design relevant to annotation workflows.
  
  
• Evaluation of code quality ownership, debugging ability, and architecture thinking.
  
  
• Discussion of past leadership experiences with emphasis on hands-on involvement.
  
  
• Optional: sharing personal AI projects or demonstrations.
  
  

Apply If You Want To

• Lead meaningful coding workstreams that directly impact LLM capabilities.
  
  
• Build and architect high-quality data systems and workflows.
  
  
• Work with a fast-moving, technically strong team shaping the future of AI.

 

Values:

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

 

Advantages of joining Turing: