44 jobs for “Manufacturing”
Build the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develop solvers in differentiable or GPU-native frameworks like JAX or Warp, using commercial and open-source CFD tools, while collaborating closely with ML researchers in a research team.
JAX · NVIDIA Warp · OpenFOAM +2
Customer-facing role owning the full journey from onboarding and change management to roadmap planning and contract preparation, working alongside simulation, software, ML engineers and data scientists. Translates complex engineering and physics challenges into product opportunities, tracks engagement and grows strategic accounts. Hybrid, based in NYC or the Bay Area.
Develops production-grade ML models and pipelines for physics simulation, working with research scientists and simulation engineers. Involves scaling training and inference across multi-GPU/multi-node distributed systems, optimising from job scheduling down to CUDA/Triton/Warp kernels, and building cloud infrastructure on CoreWeave and AWS.
AWS · Azure · GCP +7
Builds and owns the LLM access layer for agents on the PhysicsX platform, serving self-hosted open models and routing each task to the best-fitting model or combination. Sets technical direction for inference engines like vLLM and SGLang and serving platforms such as KServe, including air-gapped deployments, GPU autoscaling, batching, caching and quantisation. Works with Research and Post-Training specialists to move tuned models into production routes.
vLLM · SGLang · KServe +6
Delivery-focused role embedding physics-aware AI models into customer tools, building reliable ML data pipelines and working with 3D point-cloud and mesh data. Spans data science and software engineering, translating R&D into reusable libraries and products, with regular on-site customer travel.
TensorFlow · MLflow · Spark +6
Builds and deploys machine learning systems for industrial physics challenges, designing reliable data pipelines and working with 3D point-cloud and mesh data. Partners directly with customers on-site to embed AI models into practical tools, translating R&D outputs into reusable libraries and products. Requires Python, cloud, and MLOps experience with frequent travel.
TensorFlow · MLflow · Spark +6
Partners with engineering teams to embed security into CI/CD pipelines, lead threat modeling and secure design reviews for web apps, APIs and cloud services, and run the product vulnerability lifecycle. Also drives secure coding standards, delivers hands-on training, and engages with customers during security reviews.
GitHub · GitLab · Semgrep +3
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Works directly with customers on-site, leads scoping and architecture, and mentors engineers and data scientists. Tech stack includes Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow.
Python · PyTorch · Pandas +5
Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation engineers and customers. Owns data pipelines and production-ready models, and travels to customer sites roughly 3-4 weeks per quarter to co-develop solutions on-site.
NumPy · SciPy · Pandas +2
Develops multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches, non-Newtonian rheology and coupled reactive physics. Owns meshing strategy, parametric CAD-coupled simulation pipelines, HPC-scale transient runs and surrogate/ML-CFD workflows, working directly with customers to scope and validate models against experimental data.
Star-CCM+ · OpenFOAM · Fluent +5
Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices, and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus quarterly on-site travel.
FastAPI · Helm · Kubernetes +3
Contributes to high-fidelity CFD simulations for marine propulsion projects, including propeller and hull-propeller interaction, using OpenFOAM for steady-state and transient cavitating cases. Builds models from geometry clean-up and meshing through post-processing, and works at the intersection of CAE and data science to generate simulation datasets for machine learning surrogates. Joins at the founding stage of the Singapore team, collaborating with data scientists and ML engineers and occasionally travelling to customer sites.
OpenFOAM · Star-CCM+ · Fluent +4
Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate industry challenges into product opportunities, tracking engagement and measuring value. Based in Singapore, bridging advanced AI capabilities and practical engineering applications.
Owns high-level research work-streams, setting technical direction and roadmaps while guiding junior team members. Builds deep learning and probabilistic models of physical systems, collaborating with ML and simulation engineers to translate physics problems into mathematical formulations and production code. Requires a PhD and a strong publication record.
PyTorch · CUDA · JAX +4
Builds high-fidelity CFD models from geometry clean-up and meshing through simulation and post-processing, using Star-CCM+, OpenFOAM or Fluent and parametric CAD tools. Works alongside data scientists and ML engineers to generate simulation datasets for deep learning surrogates, running jobs on cloud and on-premise HPC, with occasional international travel to customer sites.
Star-CCM+ · OpenFOAM · Fluent +4
