Tech Lead Manager, Frontier Data Products - Multimodal

Mercor

New York, Northern (NY, KY)

Hybrid

USD 180,000 - 240,000

Full time

3 days ago

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Benefits offered by this job

Bi‑annual performance bonus

Generous equity grant

Up to Relocation bonus

Housing bonus

Meals stipend

Health insurance

Relocation assistance

Gym/Wellness stipend

Job summary

Mercor is seeking a Tech Lead Manager to guide the Frontier Data Products team in building scalable multimodal data systems. This player‑coach role balances production coding, architecture, and people leadership to deliver trustworthy data products at scale.

You’ll own strategy, design robust pipelines for images, video, audio, and documents, and drive cross‑functional collaboration with ML, product, and operations teams in a fast‑paced, in‑person work environment.

Qualifications

Experience leading an engineering team while remaining hands-on and technically active.
Strong background designing and operating production backend, distributed, and data-intensive systems.
Experience with large unstructured data, asynchronous processing, metadata/versioning, or compute-heavy workflows.
Proven ability to recruit, coach, and retain engineers while maintaining high performance.
Track record taking ambiguous products from architecture to launch and sustained production operation.

Responsibilities

Set technical and product strategy for multimodal data products.
Design systems covering input to delivery across image, video, audio, documents, and mixed media.
Create reusable abstractions while preserving modality-specific quality.
Build systems with automated evaluation, model-assisted checks, and expert review.
Ensure traceability of outputs: provenance, changes, evaluation, and rationale.
Own reliability, performance, and cost of long-running workflows.
Stay hands-on by writing production code and leading design reviews.
Mentor engineers with clear expectations and ownership.
Collaborate with product, ML, ops, and customer teams to turn needs into durable capabilities.
Recruit and onboard engineers to raise the team’s bar.

Skills

Leadership

Backend architecture

Multimodal data processing

Distributed systems

Code reviews & mentoring

Tools

AWS

Kubernetes

Data pipelines

Job description

About Mercor

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast‑paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in‑person five days a week in our San Francisco, NYC, or London offices.

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

Experience managing a strong engineering team while remaining an effective, hands‑on technical leader.
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.
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