Scientist II, Mechanics & Extreme Materials (Materials Science)

TL;DR

Scientist II, Mechanics & Extreme Materials (Materials Science): Driving closed-loop learning for extreme materials with an accent on hard, wear-resistant, and corrosion-resistant coatings. Focus on developing characterization workflows and integrating metallurgical data into autonomous AI systems to accelerate material discovery.

Location: Cambridge, MA, USA

Salary: $128,000 - $172,000 USD

Company

hirify.global is building Scientific Superintelligence to autonomously execute the scientific method across medicine, materials, and energy.

What you will do

• Drive the strategy for closed-loop campaigns on anti-wear and anti-corrosion materials.
• Develop and optimize testing workflows for extreme environment materials, focusing on microstructural, mechanical, and tribological analysis.
• Collaborate with ML scientists and engineers to integrate characterization outputs into autonomous closed-loop workflows.
• Lead experimental design and analysis to extract key materials properties for ML training.
• Troubleshoot characterization instrumentation to sustain high-throughput operational performance.
• Maintain accurate laboratory records and ensure safety and regulatory compliance.

Requirements

• PhD in Materials Science, Metallurgy, Mechanical Engineering, or a related field.
• 3+ years of post-PhD or industry experience.
• Proficiency in nanoindentation-based mechanical characterization of thin films and bulk materials.
• Deep expertise in microstructural characterization of metal alloys using SEM, TEM, and EBSD.
• Strong grounding in physical metallurgy and ceramics science, including phase equilibria and deformation mechanisms.
• Ability to translate structure-property relationships into experimental design decisions.

Nice to have

• Experience with high-throughput or autonomous experimental workflows.
• Proficiency in Python for data analysis and workflow automation.
• Exposure to coating deposition and bulk alloy synthesis techniques.
• Experience with ML-guided experimental design or active learning frameworks.
• Familiarity with CALPHAD modeling (Thermo-Calc, Pandat).

Culture & Benefits

• Competitive base compensation with bonus potential.
• Generous early-stage equity.
• Comprehensive U.S. and International benefits.
• Fast-paced startup environment tackling problems of historic importance.
• Company culture guided by truth, trust, curiosity, grit, and velocity.