Join an innovative team as a Mass Spectrometry Scientist, where your expertise in analytical chemistry and mass spectrometry will play a crucial role in supporting AI training and evaluation for scientific applications. This unique position allows you to work flexibly in a remote environment, helping to train and refine advanced AI systems by leveraging your deep domain knowledge and analytical skills.

• Apply mass spectrometry expertise to train, evaluate, and enhance AI models that support scientific research and analytical workflows.
• Develop, review, and validate scientific prompts, datasets, and outputs focused on mass spectrometry and analytical chemistry.
• Interpret and analyze mass spectrometry data, spectra, and results to ensure accuracy in AI-generated scientific content.
• Provide expert feedback on AI outputs, ensuring scientific rigor, correct methodologies, and precise terminology.
• Design and review mass spectrometry scenarios, problems, and datasets for AI model training purposes.
• Collaborate with interdisciplinary teams including AI researchers, data scientists, and engineers to optimize model performance in scientific domains.
• Document evaluations, insights, and best practices to continually improve AI systems and training materials.

• Advanced knowledge and hands-on experience with mass spectrometry techniques and instrumentation.
• Strong analytical and problem-solving skills, with expertise in interpreting complex mass spectrometry datasets.
• Deep understanding of analytical chemistry principles and MS-based experimental workflows.
• Excellent written and verbal communication skills, with the ability to convey complex scientific concepts clearly.
• Experience in scientific research, analytical laboratories, or related technical environments.
• Ability to work independently while contributing effectively to a remote, collaborative team setting.
• MS or PhD in Chemistry, Biochemistry, Analytical Chemistry, or a related scientific field.

• Experience with mass spectrometry data analysis platforms such as Xcalibur, MassLynx, or similar tools.
• Background in proteomics, metabolomics, pharmaceutical, or environmental analysis using mass spectrometry.
• Familiarity with AI, machine learning workflows, or scientific data annotation and evaluation.