247 jobs for “ML Architect”
PhysicsX Singapore
Builds and operates a SLURM-on-Kubernetes HPC platform with 304 B200 GPUs, split evenly between platform engineering and hands-on support for researchers. Work covers cluster reliability, containerised job environments, high-performance storage and networking, and debugging distributed training and data generation workloads.
PhysicsX London
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines with Python, PyTorch, Kubeflow and fastAPI. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.
NVIDIA United Kingdom
You will own a small portfolio of strategic software companies, acting as their trusted technical advisor to integrate NVIDIA's AI platform, open models, SDKs and NIMs into their products. The role blends hands-on agentic AI and GPU-computing depth with developer advocacy, ecosystem mapping and commercial storytelling to engineering and C-suite audiences.
Databricks London
Lead a delivery team of 8+ engineers building and productionising data and AI solutions on the Databricks platform for enterprise customers. The role blends hands-on technical oversight of Spark, Python/Scala, cloud and MLOps architectures with professional services delivery metrics, hiring and coaching. Hybrid working in London, with accountability for bookings, revenue, margin and customer satisfaction.
Isomorphic Labs Cambridge, United States
Lead computational drug design programs from initiation through to clinical candidate selection, applying AI-first approaches and shaping the company's ML drug design engine. Work cross-functionally with ML, biology and chemistry teams, with optional people management of 2-3 computational chemists.
Isomorphic Labs Cambridge, United States
Lead DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments while integrating PK, PD and toxicology data for dose and safety predictions. Work within an AI-first preclinical team, shaping ADME predictive models and authoring regulatory documents to advance candidates toward first-in-human trials.
Databricks London
Enterprise sales role driving adoption of Lakebase, a fully-managed serverless Postgres service for operational and AI-native applications. Partners with regional Account Executives to run multi-threaded sales cycles, orchestrate POCs for OLTP and reverse ETL workloads, and compete against legacy and cloud-native databases. Also enables the field and shapes territory plans with Product, Marketing and Partner teams.
Faculty London
Drives technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. Leads capability testing for Frontier AI models, builds scalable ML infrastructure and multi-agent tooling, and advises senior client stakeholders while mentoring engineers.
Wayve London
Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.
Wayve London
Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, prototypes and cross-functional alignment across perception, calibration and validation teams.
Faculty London
Deliver bespoke, production-grade machine learning systems for government and national security clients, covering the full ML lifecycle from scoping and architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and defining standards for deploying ML at scale.
OpenAI London
Partner directly with engineering organizations to design, build, and deploy AI-powered software development workflows using Codex, from use-case selection through prototyping, evaluation, and production rollout. Combines hands-on coding in Python with customer leadership, building evaluation harnesses, integrations, and reusable architectures while feeding deployment insights back to Product and Research teams.
Relation Therapeutics London
Builds and scales generative and predictive models of cellular behaviour, implementing and optimising large neural networks and distributed training infrastructure. Acts as a bridge between ML research and production, profiling GPU workloads and optimising inference for use by data scientists and biologists on multi-modal biological data.
Helsing Berlin, Germany
Integrates state-of-the-art AI and software into complex customer systems, working directly with avionics engineers and partners to understand unfamiliar data structures, APIs and network protocols, then building adapters to connect them to Helsing's cloud infrastructure. Owns delivery end-to-end, from formalising requirements and fixing bugs to shipping features and running technology demonstrations in simulations or on real systems.
Latent Labs London
Work at the interface between frontier generative models and pharmaceutical/biotech customers, deploying, adapting and fine-tuning models in customer environments. Build production-grade API integrations, model-serving infrastructure and ML data pipelines, while acting as technical point of contact for partners. Combines deep ML research with customer-facing delivery in an interdisciplinary team.
