About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.

We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

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.

Inclusive Hiring at Mecka

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Mecka regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.