Special Projects Lead, Sciences

Mecka•New York, NY

About The Position

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. We’re hiring a Special Projects Lead to build and run scientific programmes that produce high-quality data for AI and robotics. You’ll work across scientific partnerships, programme development and laboratory operations, taking initiatives from an initial brief through launch and ongoing delivery. This is a hands-on strategy and operations role. You’ll assess opportunities, set operating priorities and work through the practical challenges of getting new programmes running. You should be comfortable shaping a plan, making decisions with incomplete information and doing the work needed to deliver it.

Requirements

Scientific fluency from laboratory experience or sustained work with experimental scientists.
A track record of launching and running programmes or operations, with responsibility for delivery, quality and cost.
Experience managing external partnerships and coordinating people, vendors and operational resources.
Evidence of prioritizing work, evaluating tradeoffs and making sound decisions under uncertainty.
Willingness and ability to execute directly, including resolving practical problems alongside coordinating others.

Nice To Haves

Scientific or laboratory operations, research partnerships or technical special projects.
Founder or early startup experience involving substantial operating responsibility.
Building and improving operations across multiple sites or international partner teams.

Responsibilities

Develop scientific programmes.
Translate commercial and scientific objectives into practical plans, milestones and operating requirements.
Build and manage partnerships.
Develop relationships with scientific organisations, coordinate agreements and onboarding, and manage ongoing performance.
Launch new initiatives.
Establish workflows, coordinate equipment and resources, train teams and resolve readiness gaps.
Own operating performance.
Manage quality, throughput, schedules and cost.
Identify bottlenecks and improve how programmes run.
Coordinate people and resources.
Manage partner teams, vendors and logistics across locations.
Keep commitments clear and resolve issues directly.
Make informed operating decisions.
Evaluate opportunities, test assumptions and use delivery evidence to decide what to improve, expand or stop.