Autonomous Science Lead

Mecka•New York, NY
•$160,000 - $200,000

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 an Autonomous Science Lead to make automated laboratory work scientifically valid and reliable. You’ll lead experimental methods and scientific operations, combining hands-on laboratory experience with an understanding of AI, robotics and automation. You’ll work directly with instruments, protocols and experimental results, alongside scientists and engineering specialists. The role requires someone who can establish sound scientific methods, troubleshoot practical problems and turn promising workflows into dependable operations.

Requirements

  • Substantial hands-on experimental work, with ownership of methods, controls, reproducibility and interpretation.
  • Experience running automated laboratory operations, including instruments, resources, staffing and quality procedures.
  • Practical experience with AI and robotics in laboratory automation or experimental systems.
  • Working knowledge of reinforcement learning and model evaluation, sufficient to contribute to scientifically meaningful tasks and assessments.
  • Ability to work directly at the bench and with instruments, and translate scientific requirements into specifications for engineers.

Nice To Haves

  • Experience building RL environments, robotic benchmarks or model-evaluation tools.
  • Scientific leadership in a contract research organisation, research core or shared instrumentation facility.
  • Improving experimental reliability, turnaround or cost across different operators, instruments or operating conditions.

Responsibilities

  • Own experimental methods. Select and adapt protocols, design controls and define scientific acceptance criteria.
  • Develop automated workflows. Assess and qualify instruments, labware and automation with engineering specialists.
  • Establish scientific validity. Evaluate results, investigate variability and distinguish execution problems from scientific failures.
  • Lead laboratory operations. Plan staffing, equipment, materials and operating requirements. Establish training, documentation and safe working procedures.
  • Troubleshoot hands-on. Diagnose problems at the bench and across instruments, hardware and software. Coordinate technical fixes and verify their effects.
  • Improve operating performance. Assess reproducibility, throughput, manual effort and cost. Identify which methods are ready for routine use and where further development is needed.
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