PhysicsX
GrowthAI for physics simulations in aerospace, automotive, and energy. FDEs embed with engineering teams to replace or dramatically accelerate CAE workloads. CFD, FEA, crash simulation. With physics-informed neural networks trained on the customer's own simulation history.
Signals from job descriptions
Patterns mined from PhysicsX's open FDE postings
- 01
PhD in physics, engineering, or mathematics is required (not preferred) in most FDE roles. The steepest academic bar of any company profiled here.
- 02
CFD and FEA experience is listed alongside Python skills. Domain knowledge of physical simulation is as important as software engineering.
- 03
HPC cluster experience is a hard requirement, meaning FDEs operate at the intersection of supercomputing and ML, not just cloud-native AI.
Tech stack
Inferred from job descriptions
Languages
AI / ML
Cloud & infra
Tools & integrations
Sectors
Hiring regions
- United States
- UK & Europe
- Asia-Pacific
Seniority mix
- Mid-level / unspecified4
- Senior2
Open roles · 6 total
Forward Deployed Software Engineer
New York
Forward Deployed Software Engineer
London, United Kingdom
Forward Deployed Software Engineer
Singapore
Forward Deployed Software Engineer
San Francisco, CA
Senior Forward Deployed Software Engineer
New York, United States · Senior
Senior Forward Deployed Software Engineer
New York, NY · Senior
Put an embedded AI team on your roadmap
Forward-deployed engineers to deploy, AI-native engineers to build, and on-demand QA pods to validate, embedded with your team, starting the same day.