Luminarycloud

Senior/Principal Forward Deployed Engineer - Applied AI/ML

San Mateo, CA · Principal · Full-time

Sponsorship not specifiedDetected 14 days ago

PythonMachine LearningDeep LearningPyTorchA/B TestingFEACFDResearch

About the role

Full-time position | San Mateo, CA (Onsite) JOIN THE REVOLUTION IN ENGINEERING INNOVATION Luminary helps engineering companies be more competitive by getting to market faster, creating better products, and reducing development risk.
Luminary is a Series B company headquartered in San Mateo, California.
You operate at the boundary of cutting-edge research and applied delivery - staying connected to the frontier of physics-informed ML while making sure your work ships and gets used.

As a Senior/Principal Applied AI/ML Scientist on Luminary's Applied AI/ML team, you build the Physics AI models that power customer outcomes.
You take real customer engineering problems, design and train the right model architectures, and partner with the team to deploy those models into production engineering workflows.
Own model development for Physics AI engagements: architecture selection, training pipeline design, hyperparameter tuning, evaluation, and validation against ground-truth simulation.
Partner with Data & Platform engineers to operationalize training pipelines, model registries, and inference serving.
Embrace co-engineering: work side-by-side with customer data scientists and engineers, sharing methodology and building model literacy on the customer side.
YOUR IMPACT As a Senior/Principal Applied AI/ML Scientist on Luminary's Applied AI/ML team, you build the Physics AI models that power customer outcomes.
architecture selection, training pipeline design, hyperparameter tuning, evaluation, and validation against ground-truth simulation.

Hands-on experience training and deploying models on engineering or scientific data - surrogate models, neural operators, graph neural networks, diffusion models, or related architectures.
Experience with distributed training, GPU workloads, and modern ML infrastructure (experiment tracking, model registries, inference serving).

Advanced degree (MS or PhD) in Computer Science, Applied Math, Physics, Engineering, or related quantitative discipline.
Experience with physics-informed AI/ML frameworks (e.g. PhysicsNeMo, JAX-based scientific ML stacks) or foundation model fine-tuning pipelines for scientific data.
Prior experience in applied research roles at engineering, simulation, or scientific computing companies.
Track record of shipping models into production engineering workflows.
rigorous experimentation, careful evaluation, honest reporting of what works and what does not.
Customer-facing presence
comfortable explaining model architectures and limitations to engineering audiences.
Self-starter mentality, persistent through iteration, willing to travel occasionally to customer sites.

Collaborate with Luminary Research to apply state-of-the-art techniques - neural operators, diffusion models, geometric deep learning, latent representations - to real customer problems.

We do this through our Physics AI platform - the fastest and easiest way to build and deploy models that understand and instantly predict physical reality with precision.
Our customers span industries from automotive and aerospace to defense, industrial, semiconductors, and energy - ranging from hyper-growth startups to Fortune 100 enterprises.

This listing is sourced directly from Luminarycloud's careers page and normalized into a canonical job model.