Forward Deployed Data Engineer

Department: Platform Engineering & Infrastructure

Location: New York

Compensation: $180K – $250K • Offers Equity

Employment Type: FullTime

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.

We partner with leading AI labs and robotics companies to deliver high-quality, real-world datasets used to train, evaluate, and deploy robotic systems - where model performance is dictated by data quality.

The Role

We are hiring a Forward Deployed Data Engineer to operate on the frontier with customers: take messy, real-world capture data - much of it raw video - and turn it into beautiful, reliable, model-ready datasets, while owning the technical relationship end-to-end.

This is a senior, high-trust role with significant autonomy. You'll combine data engineering, hands-on analysis, and product judgment to deliver datasets customers can train and ship on - and to make our delivery systems more reliable every time you do.

What You'll Work On

Customer Delivery & Technical Ownership

• Own the end-to-end delivery of customer datasets: requirements, validation, iteration, final handoff.

• Be the technical point of contact: communicate clearly, set expectations, and close loops.

• Turn one-off customer needs into durable internal improvements - tooling, pipelines, and standards that make every future delivery faster and safer.

Data Systems & Pipelines

• Build, debug, and harden data pipelines across ingestion, transformation, QA, and export.

• Work fluently across storage and database paradigms (SQL + NoSQL + object storage) and pick the right tool for the job.

• Establish reliable dataset "contracts": schemas, versioning, provenance, and reproducible builds - so every dataset has a clear source of truth.

Dataset Quality & Signal

• Define and measure what makes a dataset good for a given task: coverage, diversity, balance, label fidelity, and fitness for the customer's model.

• Build quality scorecards and coverage/diversity reports that make dataset health legible to customers and internal teams.

• Query and slice large corpora to maximize customer fit - surface exactly the data that matches a target distribution, not just bulk volume.

• When the signal a customer needs is missing or weak in the raw video, diagnose it and partner with the perception/ML pipeline teams to extract or improve it upstream.

Who You Are

Required Background

• 5+ years in data engineering and/or backend engineering (or equivalent impact).

• Strong experience with large data systems, pipelines, and analytical workflows.

• Strong SQL proficiency and comfort across multiple database/storage paradigms.

• Excellent engineering judgment and debugging ability in production systems.

• Genuine data taste - you can look at a dataset and reason about whether it's complete, balanced, and trustworthy, not just whether the job ran.

Strong Signals

• You've owned high-stakes customer deliveries with autonomy and trust.

• You can translate ambiguous requirements into crisp dataset specs and execution plans.

• You have strong product instincts and care about polish: "would I trust this dataset?"

• You're comfortable working with unstructured, real-world data - especially video.

Nice to Have

• Working literacy in video understanding, embeddings, and encoders - enough to reason about what a dataset teaches a model and where signal is missing.

• Experience building data-quality, coverage, or diversity tooling.

• Background adjacent to ML, computer vision, or robotics data.

Why This Role

• Own the customer-facing delivery loop for world-class robotics datasets.

• High autonomy, high trust, and direct impact on customer success and revenue.

• Work across the full stack of the problem: data, pipelines, analysis, and delivery quality.

• Sit at the exact point where raw, messy, real-world data becomes the thing that makes embodied-AI models work.