60 jobs
PhysicsX New York, United States US$200,000 – US$300,000 pa
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.
PhysicsX New York, United States US$200,000 – US$250,000 pa
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.
Cohere London
Builds and owns the training framework powering frontier-scale language models, spanning distributed training abstractions, checkpointing, and performance profiling across thousands of GPUs. Works at the intersection of large-scale training, distributed systems, and HPC, partnering with infra, research, and deployment teams on tooling that speeds up ML development.
Cohere London
Drive safety research for agentic LLMs, focusing on data generation, post-training algorithms and evaluation methods so models that access external tools and act in the world remain fair, trustworthy and secure. Work with cross-functional ML, data annotation, product and policy teams on a small, autonomous team, requiring strong statistics, software engineering and Python/PyTorch skills.
ElevenLabs United Kingdom
Owns and operates NVIDIA GPU clusters across bare metal and rented capacity, handling provisioning, scheduling, monitoring and capacity planning. Builds automation for node health checks, draining and burn-in, and tunes the stack beneath training code including CUDA, NCCL, InfiniBand/RoCE and Slurm. Also benchmarks rented GPU capacity and does hands-on datacenter hardware work.
ElevenLabs United Kingdom
First dedicated analytics partner to the Finance function within a central Data team, owning revenue and ARR reconciliation, cohort and retention economics, and pricing experiments. Builds forecasting and scenario models used directly by FP&A for planning and board reporting, working with SQL, Python, Stripe, Salesforce and a dbt-modelled warehouse.
PhysicsX New York, United States 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.
PhysicsX Singapore
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.
PhysicsX London
Builds and validates multiphase CFD and coupled CFD-DEM models, covering geometry clean-up, meshing, simulation, post-processing and experimental validation for granular and particle-laden systems. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for ML surrogate models on cloud and HPC resources, while working on-site with customers and mentoring junior colleagues.
PhysicsX New York, United States
Builds and runs high-fidelity CFD models from geometry clean-up and meshing through simulation and post-processing, using Star-CCM+, OpenFOAM or Fluent plus parametric CAD and Python/Java automation. Works with data scientists and ML engineers to generate simulation datasets for deep learning surrogates, running jobs on the Flux cloud platform and on-premise HPC, and supports customer engagements with occasional travel.
PhysicsX Singapore
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.
PhysicsX Singapore
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.
PhysicsX Singapore
Builds and operates a SLURM-on-Kubernetes HPC platform running 304 B200 GPUs for large-scale distributed training and CAE data generation. Splits time between platform engineering — hardening, storage, networking, observability — and hands-on debugging of job failures and throughput bottlenecks alongside researchers.
PhysicsX London
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.
PhysicsX London
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.
