Machine Learning Jobs

• New York, United States
• Hybrid
• Lead

Lead the ML approach to manufacturing and MRO data, taking models from design through deployment in customer production environments across cloud, on-prem and edge. Work with sparse, drifting sensor and process data, fusing physics simulation with shop-floor measurement, and set uncertainty quantification and validation standards. Requires travel to customer sites 3-4 weeks per quarter and mentoring of engineers and data scientists.

PyTorch · Pandas · FastAPI +2

• San Francisco, United States
• Hybrid
• US$150,000 – US$190,000 pa

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

• London
• Hybrid
• Senior
• Permanent

Develops next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Works across diffusion, transformer and hybrid architectures, optimising inference latency and building interactive models for reinforcement learning and safety evaluation. Involves setting technical direction, mentoring researchers and publishing at top venues.

PyTorch · GAIA · Transformer +1

• London
• Hybrid
• Senior · manages people
• Permanent

Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, coordinating with Product, Safety and Release stakeholders.

Python · SQL

• New York, United States
• Hybrid
• US$150,000 – US$190,000 pa
• Mid-level

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

• New York, United States
• Hybrid
• US$200,000 – US$300,000 pa
• Lead

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

• New York, United States
• Hybrid
• US$200,000 – US$250,000 pa
• Senior

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

• New York, United States
• Hybrid · 2–3 days in office
• US$120,000 – US$240,000 pa

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

• Singapore
• Hybrid
• Lead

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

• Singapore
• Mid-level

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

• Singapore
• Mid-level

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.

• London
• Hybrid
• Lead

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

• New York, United States
• Hybrid · 2–3 days in office
• Mid-level

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

• London

Owns the product capability for post-training LLMs, turning research methods into deployable model improvements for customers. Builds reliable training harnesses, synthetic-data pipelines and evaluation workflows, applying SFT, preference optimisation, RLHF/RLAIF and verifier-based approaches. Works closely with Research and platform teams, with a roadmap spanning SaaS, VPC and air-gapped deployments.

PyTorch · LLMs · SaaS +1

• Singapore
• Hybrid
• Lead

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics and simulation challenges into mathematical formulations. You will develop deep learning and probabilistic models for physical systems, run large-scale experiments, and own research workstreams while publishing and presenting to customers and the community.

NumPy · SciPy · Pandas +4