Senior Physical AI Engineer - Digital Twins & ML

McKinsey; Dallas (TX); On-site; USD 173,000 - 211,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits package

Mentorship and growth opportunities

Job summary

McKinsey & Company seeks a highly qualified scientist/engineer to apply physics-based modeling and ML to help leading industrial clients tackle complex engineering challenges. You will lead technical workstreams, develop multi-physics simulations and digital twins, and translate computational insights into actionable recommendations.

You will work in a collaborative environment within the Scientific and Physical AI team, contributing to a first-of-its-kind physics AI capability while growing

Qualifications

• Advanced graduate degree in computational mechanics, materials science, or related field.
• Experience developing engineering or scientific code (Python/C++).
• Fluency in machine learning, data science, and statistical sampling.
• Experience with simulation, PyTorch; ML/AI knowledge a plus.
• Strong organization, data-driven decision making, and communication skills.
• Willingness to travel and work across time zones.

Responsibilities

• Lead technical workstreams on client engagements and build multi-physics simulation frameworks.
• Develop surrogate models and machine learning solutions for engineering systems.
• Deploy scalable tools on HPC infrastructure and translate insights into client solutions.
• Collaborate across teams to deliver measurable impact for clients.

Skills

Python

C++

Machine learning

Data science

PyTorch

Time management

Communication

Education

M.S. or Ph.D. in computational mechanics or related field

Tools

PyTorch

Excel

PowerPoint

Job description

McKinsey & Company seeks a highly qualified scientist/engineer to apply physics-based modeling and ML to help leading industrial clients tackle complex engineering challenges. You will lead technical workstreams, develop multi-physics simulations and digital twins, and translate computational insights into actionable recommendations.

You will work in a collaborative environment within the Scientific and Physical AI team, contributing to a first-of-its-kind physics AI capability while growing