Experience scaling foundation models at large scale
Proficiency in python with pytorch or jax frameworks
The role involves building AI-driven simulation software stacks that enable high-fidelity multi-physics modeling across industries like Aerospace and Automotive
Job Summary
The role involves building AI-driven simulation software stacks that enable high-fidelity multi-physics modeling across industries like Aerospace and Automotive.
Candidates will work closely with research scientists to design, build, and scale foundation models while transforming prototypes into robust, optimized implementations.
The company offers a flat hierarchy structure where good ideas win regardless of origin, alongside comprehensive benefits including equity options and enhanced parental leave.
Matching Summary
The role involves building AI-driven simulation software stacks that enable high-fidelity multi-physics modeling across industries like Aerospace and Automotive.
Salary
Equity options available; 10% employer pension contribution; Not specified base salary
Skills & Requirements
Must-have
MSc or PhD in CS, ML, Physics, or related field
Experience scaling foundation models at large scale
Proficiency in Python with PyTorch or JAX frameworks
Knowledge of distributed computing frameworks like MPI or Dask
Strong background in high-performance CPU/GPU cluster computing
Nice-to-have
Experience with federated learning implementations
Familiarity with C/C++ for computer vision tasks
Background in scientific computing or numerical physics
Ability to mentor junior engineers and foster growth
Experience with cloud platforms AWS, Azure, or GCP
Key Requirements
MSc or PhD in Computer Science, Machine Learning, Physics, or Engineering
Minimum 2 years of professional experience in data-driven roles
Proven track record in parallelized or distributed model training