41 jobs
PhysicsX New York, United States US$150,000 – US$250,000 pa
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.
PhysicsX London
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.
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 London
Builds and operates the platform every team ships on, running Kubernetes clusters including GPU fleets for training and inference across cloud and on-prem. Sets up compute, networking, IAM and data systems for other teams, and writes Python or Go tooling to make infrastructure self-serve. Works hands-on in a flat team on cluster builds and cloud migrations.
ElevenLabs United Kingdom
Owns the data infrastructure behind frontier AI models, building large-scale pipelines for collecting, filtering and transforming training datasets. Also trains classifiers, quality filters and labeling models, and designs curation strategies like deduplication and quality scoring. Fully remote, with tooling work letting researchers explore and train on massive datasets.
PhysicsX Singapore
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.
PhysicsX Singapore
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.
PhysicsX Singapore
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.
PhysicsX Singapore
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.
Cohere London
Builds and optimizes the synthetic data pipeline behind Cohere's frontier language models, running scalable inference on large GPU clusters and transforming web and code data with generative models. Involves data ablations, mixture experiments and model evaluation to improve token efficiency and training throughput, working closely with researchers and engineers.
Cohere London
Owns key components of a large-scale web data pipeline for pre-training language models, covering extraction, parsing, deduplication and filtering of noisy internet corpora. Analyses data composition and quality across domains, languages and time periods, and studies its impact on downstream model performance alongside research and evaluation teams.
Cohere London
Owns the integration pipeline for an enterprise AI workspace platform, building and maintaining tools that connect external APIs and data sources to agentic systems. Writes evals and tests to catch regressions, tunes tool descriptions, and helps other engineers add integrations while raising team standards.
Cohere London
Founding Solutions Architect for the Nordics, owning the technical relationship with enterprise and government customers. Leads design and deployment of pilots, maps customer problems to AI solutions, and works with account executives, partners and product teams to drive adoption of LLM technology.
Cohere United Kingdom
Own the design, build and deployment of LLM-powered agentic workflows for enterprise customers, integrating models with tools, APIs and sensitive data sources. Work across the full product lifecycle on the North AI workspace platform, building reliable, observable and auditable agents, with up to 20-40% travel to customer sites.
