Tech Lead, AI Data Products

About Mercor

Mercor’s mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world’s leading AI labs. Now, we’re bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We’re solving problems few companies have encountered, with the opportunity to influence what the world’s most advanced AI systems become capable of doing. We’re looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You’ll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

About the Role

Frontier models increasingly depend on data that goes beyond text: images, video, audio, documents, and combinations of these modalities. Turning that raw material into useful data products is technically difficult. Each modality has different formats, quality failures, processing costs, privacy considerations, and review workflows. The final product still needs to be consistent, traceable, and trustworthy. Mercor’s Frontier Data Products team builds the systems that make these products possible.

As Tech Lead Manager, you will lead the team responsible for turning complex multimodal inputs into reliable, customer-ready data products at scale. This is a player-coach role, split roughly evenly between technical contribution and people leadership. You will write and review production code, own important architecture decisions, and help resolve the hardest production problems.

You will also hire, coach, and organize a team that can operate with clear ownership and strong independent judgment. This is a product-engineering leadership role. Applied ML is part of the system, but success is measured by the quality, reliability, and usefulness of the products delivered—not by research output alone

What You’ll Do

• Set the technical and product strategy for Mercor’s multimodal data products.

• Design systems that support the full lifecycle of image, video, audio, document, and mixed-media data—from initial inputs through processing, review, validation, versioning, and delivery.

• Create reusable abstractions across modalities while preserving the differences that matter for quality, performance, and customer requirements.

• Build quality systems that combine automated evaluation, model-assisted checks, expert review, sampling, and adjudication.

• Ensure that every output is traceable: what produced it, what changed, how it was evaluated, and why it was accepted.

• Own the reliability, performance, and cost of storage-heavy, compute-intensive, long-running workflows.

• Stay hands-on by writing production code, leading design reviews, and directly contributing to the team’s most consequential technical work.

• Manage and develop engineers through clear expectations, frequent feedback, thoughtful delegation, and meaningful ownership.

• Partner with product, ML, operations, and customer-facing teams to turn new customer needs into durable product capabilities rather than one-off solutions.

• Recruit and onboard engineers who raise the team’s technical and execution bar.

What Makes This Role Different

• You will shape both the multimodal product architecture and the engineering team building it.

• The technical challenge extends beyond moving large media files. The system must preserve context, relationships, provenance, and quality across different modalities and transformations.

• Customer requirements and available models will evolve quickly. The architecture must support new products without requiring the team to rebuild the system for every use case.

• The team’s work sits directly between complex real-world inputs and the data products delivered to frontier AI customers.

What Success Looks Like

• The team can launch support for a new modality or product without building an entirely separate system.

• Product quality is measurable, explainable, and auditable across human and model-assisted workflows.

• Large, long-running jobs are observable and recoverable, with failures detected before they affect customer deliveries.

• Customer-specific work produces reusable capabilities that make the next product faster to build. - Engineers own substantial areas independently rather than depending on the manager for every technical decision.

• The team improves delivery speed while maintaining clear standards for quality, reliability, privacy, and cost.

What We Are Looking For

• Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics or Statistics

• 1+ year of experience managing a strong engineering team while remaining an effective, hands-on technical leader.

• 3+ years of deep experience designing and operating production backend, distributed, or data-intensive systems.

• Experience working with large unstructured data, asynchronous processing, metadata and versioning, or compute-heavy workflows.

Nice to Haves:

• Relevant experience in at least one area such as multimedia infrastructure, computer-vision data, video or audio processing, ML platforms, annotation systems, or human-in-the-loop products.

• Strong judgment about platform boundaries: what should be generalized across modalities and what should remain modality-specific.

• A track record of taking ambiguous, zero-to-one products through architecture, launch, and sustained production operation.

• Evidence that you can recruit, coach, and retain excellent engineers while maintaining a high performance bar.

Benefits

• Generous equity grant vested over 4 years

• Health, dental, and vision insurance

• 401(k) with company match

• Unlimited paid vacation and sick days

• Parental leave for birthing and non-birthing parents

• Free mental health services

• $200 monthly wellness reimbursement

• $1.5K monthly meal stipend

• $200 monthly laundry reimbursement

• Free Equinox membership

• Up to $15K relocation bonus

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