Job description

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. The Role We’re hiring a Senior Product Engineer to build software and data products for scientific work. You’ll own products from the first user conversation through production, working across frontend, backend and data. You’ll work directly with scientists, operators and technical teams to understand their problems, make product decisions and ship useful software. The role combines full-stack engineering with scientific understanding: the products need to work reliably and preserve the information that makes scientific data meaningful. WHAT YOU WILL BE DOING: - Understand users and set priorities. Investigate scientific and operational workflows, identify important problems and turn ambiguous needs into useful product scope. - Build across the stack. Design and implement interfaces, backend services, data models and integrations. Carry products from prototype into daily use. - Develop reliable data workflows. Build processing, validation and delivery capabilities that handle complex inputs, changing requirements and operational failures. - Make data easier to use. Develop tools for reviewing scientific information, assessing quality and investigating or correcting errors. - Improve quality and automation. Work with engineering and machine-learning specialists on processing, QA and AI-assisted annotation. - Own production performance. Test, deploy, monitor and debug your software. Improve reliability, usability and operating cost as usage grows. WHAT YOU BRING: - Independently shipping full-stack products from an ambiguous problem through launch and sustained use. - Strong frontend, backend and data-modeling fundamentals, including data processing and integrations. - Scientific fluency gained through bench work or sustained software development with experimental scientists. - Product judgment: understanding user needs, choosing a useful scope and making technical tradeoffs. - Hands-on responsibility for testing, deployment, monitoring and production debugging. EVEN BETTER IF YOU HAVE: - Scientific software used in everyday laboratory or research work. - Founder or early engineering experience with responsibility for users, architecture and delivery. - Instrument integrations, experimental data systems or tools for reviewing complex datasets. - Practical AI features that allow users to inspect, validate and correct outputs. If you don't check every box above but believe you can do the job, we encourage you to apply — we're looking for capability and trajectory, not a perfect checklist match. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs. We may use AI-assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.

Requirements

Must-haves

We’re hiring a Senior Product Engineer to build software and data products for scientific work. You’ll own products from the first user conversation through production, working across frontend, backend and data.
Understand users and set priorities. Investigate scientific and operational workflows, identify important problems and turn ambiguous needs into useful product scope.
Build across the stack. Design and implement interfaces, backend services, data models and integrations. Carry products from prototype into daily use.
Develop reliable data workflows. Build processing, validation and delivery capabilities that handle complex inputs, changing requirements and operational failures.
Make data easier to use. Develop tools for reviewing scientific information, assessing quality and investigating or correcting errors.
Improve quality and automation. Work with engineering and machine-learning specialists on processing, QA and AI-assisted annotation.
Own production performance. Test, deploy, monitor and debug your software. Improve reliability, usability and operating cost as usage grows.
Independently shipping full-stack products from an ambiguous problem through launch and sustained use.
Strong frontend, backend and data-modeling fundamentals, including data processing and integrations.
Scientific fluency gained through bench work or sustained software development with experimental scientists.
Product judgment: understanding user needs, choosing a useful scope and making technical tradeoffs.
Hands-on responsibility for testing, deployment, monitoring and production debugging.
Scientific software used in everyday laboratory or research work.
Founder or early engineering experience with responsibility for users, architecture and delivery.
Instrument integrations, experimental data systems or tools for reviewing complex datasets.
Practical AI features that allow users to inspect, validate and correct outputs.
If you don't check every box above but believe you can do the job, we encourage you to apply — we're looking for capability and trajectory, not a perfect checklist match.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

Platform: ashby
Effort: quick