Machine Learning Jobs

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Senior

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development with Python/FastAPI microservices, and cloud deployment using Kubernetes, Terraform and AWS/Azure, with frequent on-site travel to customer sites.

FastAPI · Helm · Kubernetes +3

• New York, United States
• Hybrid
• US$90,000 – US$130,000 pa
• Mid-level

Customer-facing role owning the full account journey for industrial clients, from onboarding and change management to executive reviews and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate engineering challenges into AI solutions, while building internal tooling to scale account operations.

• Oxford
• Hybrid · 2–3 days in office
• Permanent

Field-facing role delivering autonomous vehicle projects for industrial customers across ports, airports and yards, combining hands-on engineering at Culham with remote development and support. Involves workflow testing, stakeholder management and identifying process gaps, with domestic and international travel including the UAE.

Linux · Unix

• Manchester
• Remote
• £30,000 – £45,000 pa
• Junior

A 15-step online, self-paced AI traineeship covering Python, NumPy, Pandas, scikit-learn, Hugging Face, prompt engineering, RAG and vector databases, culminating in an AWS Certified Cloud Practitioner exam. It is a paid training course with fees, offering 1-to-1 tutor and recruitment support plus a job guarantee, rather than a salaried position.

Jupyter Notebook · VS Code · Streamlit +7

• 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

• Singapore
• Hybrid
• Senior

Build physical foundation models for industrial engineering, scaling training across multi-GPU cloud compute and turning research prototypes into robust, optimised implementations. Work at the intersection of data science and software engineering, owning research work-streams and translating results into reusable libraries, tooling and products alongside scientists, customers and partners.

PyTorch · JAX · NumPy +7

• Singapore
• On-site
• Director

Senior technical executive owning strategic Asia Pacific accounts, running time-boxed customer missions from first conversation to deployed, adopted platform. Acts as peer to customer CTOs and CIOs, navigating compliance, procurement and security reviews, and deploying into on-premise, air-gapped and sovereign environments. Reports to the executive team with no direct reports, shaping regional strategy and feeding field learnings back into product.

Kubernetes

• London
• Hybrid
• Mid-level

Owns PX's editorial calendar and writes blog posts, web pages, thought leadership, scripts and event materials, translating deep technical work into clear narratives. Leads LinkedIn and Instagram, supports executive and technical speaking engagements, and partners with Talent on employer brand storytelling. Works cross-functionally with engineers, designers and external agencies in a fast-moving, high-ownership comms team.

LinkedIn · Instagram · Figma +1

• London
• Hybrid · 3 days in office
• 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, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• Singapore

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves full-stack work with Python, FastAPI REST APIs and microservices, plus cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. Expects travel to customer sites in Asia, North America and Europe for 3-4 weeks per quarter.

FastAPI · Helm · Kubernetes +3

• Singapore
• Lead

Builds and delivers high-fidelity multi-physics CFD models, from geometry clean-up and meshing to simulation and post-processing, integrating experimental data for validation. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for machine learning surrogates. Works on-site with customers and mentors junior colleagues, with global travel up to 2-3 weeks per quarter.

Star-CCM+ · OpenFOAM · Fluent +4

• Singapore
• Lead · manages people

Lead technical delivery of physics AI solutions, architecting deep learning models and optimisation methods to predict and control physical systems. Build scalable production data pipelines, mentor junior team members, and collaborate on-site with customers across multiple regions to embed AI models into engineering tools.

NumPy · SciPy · Pandas +2

• Singapore
• Lead

Lead the deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Own scoping, architecture and success metrics for data/ML systems, mentor engineers, and work on-site with customers across North America, Europe, Asia and Oceania for 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• Singapore
• Senior

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development of Python/FastAPI REST APIs and microservices, and cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. It suits someone who can grasp complex engineering problems across industries and own solutions end-to-end.

FastAPI · Helm · Kubernetes +3