Autonomous Science Lead

mecka; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Mecka is seeking an Autonomous Science Lead to make automated laboratory work scientifically valid and reliable. You will 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, establishing sound scientific methods, troubleshooting practical problems and turning promising workflows into dependable operations.

Qualifications

• Hands-on experience with experimental methods and interpretation of results.
• Experience running automated laboratory operations, including staff and quality procedures.
• Practical experience with AI and robotics in laboratory automation or experimental systems.
• Working knowledge of reinforcement learning and model evaluation.
• Ability to translate scientific requirements into specifications for engineers.

Responsibilities

• Own experimental methods and define acceptance criteria.
• Develop automated workflows with instrumentation and automation.
• Establish scientific validity by evaluating results and investigating variability.
• Lead laboratory operations, staffing, equipment, and procedures.
• Troubleshoot bench-level issues across instruments, hardware and software.
• Improve operating performance by assessing reproducibility, throughput and cost.

Skills

Hands-on experimental work

Automated laboratory operations

AI & robotics in lab automation

Reinforcement learning knowledge

Bench work with instruments

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 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.

What you will be doing:

• 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.

What you bring:

• 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.

Even better if you have:

• 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.

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.