Autonomous Science Lead: Lab Automation & AI Systems

mecka; New York (NY); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Hands-on experimental work

Automated laboratory operations

AI & robotics in lab automation

Reinforcement learning knowledge

Bench work with instruments

Descripción del empleo

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.