Use object-oriented programming (Java or C#), Salesforce Lightning, Force.com, Apex, SOQL, JavaScript, Git, Jira, IntelliJ, CI/CD, and Salesforce REST APIs. Hackajob Ltd is a platform that connects developers with job opportunities. This Salesforce Developer role delivers complex business and technical requirements on the Force.com platform.

The role involves developing embedded software and software for high-speed network platforms, working with GPU-based infrastructure and interconnect technologies. The company builds next-generation networking solutions integrating hardware and photonics for high-performance computing systems.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments, working with Python, petabytes of data, and a large GPU cluster. They apply statistical and ML techniques, from linear models to deep learning.

DeepL★3.8 (4)· London

Work with Kubernetes, Terraform, ArgoCD, Go or Python, and AWS across hybrid on-prem and cloud infrastructure. The Hybrid Platform Engineering track builds and operates the compute layer—Kubernetes control plane, networking, storage, and core services—powering DeepL's language AI products and research. The role involves deepening the hybrid model and unifying workloads across on-prem and AWS.

You’ll train ML models, work on ML libraries and workflows, and use a GPU cluster with H100/H200/B200s. Projects are real-world machine learning applications for Jane Street’s global trading business, testing ideas against noisy financial data. No team size is stated.

Use deep learning frameworks, distributed computing, GPU-based training, and MLOps to build and deploy batch and real-time ML models. The Search & Recommendations team develops personalised recommendations, product ranking, and AI styling experiences for ASOS's online fashion platform, helping customers discover products.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

Build enterprise-grade web applications using Python (Django/FastAPI), React, TypeScript, and PostgreSQL. Develop RESTful APIs, responsive UI components, and contribute to system design, CI/CD pipelines, and performance optimization.

You’ll work with Python (Django/FastAPI), React, TypeScript, PostgreSQL, REST APIs, and CI/CD. You’ll own end-to-end feature delivery on scalable, enterprise-grade web applications.

Java (JDK 11+), multithreading, SQL/NoSQL databases (Oracle, MySQL, PostgreSQL, MongoDB, Cassandra), message queuing (Kafka, Tibco, Solace), Linux, JVM, and TDD. This tech lead role builds high-performance FX risk calculation systems for Citi’s Markets technology team, which supports global trading and risk management.

Work with Java, GitHub Copilot, Devin.AI, Citi Squad, Stylus Workspaces (Gemini, OpenAI, Claude, Llama), Docker, Kubernetes, and CI/CD. Build high-performance, real-time FX risk management systems for a greenfield platform with a 10+ year strategic commitment. As a VP, lead end-to-end delivery and technical direction.

Design, build, and optimize large-scale HPC/AI infrastructure using GPU optimization (CUDA, NCCL, GPUDirect RDMA, NVLink). You'll work with triple-digit petabyte-scale storage and massive CPU/GPU clusters, using Python, C/C++, and Linux in globally distributed data centers. This role covers HPC cluster design, performance tuning, and automation for thousands of nodes.

Work with Salesforce Lightning, Apex, SOQL, JavaScript, and the Force.com platform, with exposure to Git, Jira, IntelliJ, CI/CD practices, and Salesforce REST APIs. You will deliver solutions and manage complex business and technical requirements.

Zanders★4.5 (2)· London

Work with modern C++ (STL, templates, RAII, unit testing, build systems); Python or Java; Linux; GPU compute (CUDA, ROCm); and HPC tools (MPI, Slurm). Lead quantitative engagements designing, developing, and validating models for market risk, counterparty credit risk (CCR), CVA/XVA, margin models, and derivatives pricing across asset classes. Act as a career coach for up to three direct reports.

Imperial College London★4.2 (238)· London

Work with PyTorch, GPU kernel programming, Verilog, and NVIDIA's Holoscan Sensor Bridge to integrate FPGA-based AI-ISP accelerators with edge GPU platforms. The project targets low-latency, high-throughput sensor-to-GPU streaming for the "Sense-Decide" pipeline in edge automation.

Linux Recruit★3.0 (1)· London

Work with PyTorch, distributed training libraries, Slurm, Kubernetes, and AWS multi-node GPU clusters to architect and optimize large-scale model training pipelines. You will join a stealth AI startup at the intersection of robotics and embodied AI, building the infrastructure that powers next-generation AI breakthroughs.

Work with Python, PyTorch (or JAX/TensorFlow), RL fine-tuning frameworks like TRL or verl, and distributed multi-GPU training. The Reinforcement Learning Team advances RL, Bayesian optimisation, AI agents, LLMs, and vision-language models, applying them to AI for science, chemistry, physics, and robotics while publishing at top venues.

You will work with Python, PyTorch, PyTorch Lightning, TensorFlow, and experiment tracking tools to design and implement custom machine learning model components for Search, Retrieval, Ranking, or Content AI. You will join the Tripadvisor Experiences R&D Team, which is evolving the marketplace for travel experiences by powering how millions of users discover and plan itineraries. You will act as a technical lead and pod architect, and mentor mid-level and associate ML scientists.

You will use Python, KQL, SPL to build detection logic and automate response. You will protect Writer’s AI platform, training data, and model deployments, detecting threats like prompt injection and model extraction. You will coordinate incident response across teams and hunt for threats in GPU clusters and distributed training environments.

Work with Nvidia GB200 72NVL CX8 and AMD MIxxx architectures, coding in C, C++, C#, Java, JavaScript, or Python to benchmark, profile, and debug GPU clusters. You will help build foundational models powering Microsoft’s personalized AI assistant, Copilot, spanning training and inference infrastructure, model architecture, and data curation.

Software Engineers at Axle build core infrastructure for connecting and orchestrating distributed energy devices (vehicle charging, heating, home batteries) to participate in electricity markets. You'll work with Python, React, Docker, GCP, and Claude Code AI.

You'll work with PyTorch, the NVIDIA ecosystem, and ML infrastructure across the full model lifecycle. You'll create deep-dive articles, benchmarks, walkthroughs, and reproducible technical assets while representing the company at community events and collaborating with its internal AI Lab and partners including vLLM and SGLang.

You will design, build, and operate AWS infrastructure, engineer Kubernetes environments (EKS, Docker, Helm), and use Terraform for infrastructure-as-code. You will support critical investment and trading systems, improve CI/CD pipelines with GitHub Actions and GitOps (Argo CD), and work with databases like Snowflake, Aurora, and SQL Server. You will take end-to-end ownership of production systems, solve complex problems across distributed environments, and influence cloud architecture and reliability standards.

Tripadvisor★3.9 (142)· London

You will work with Python and PyTorch/TensorFlow, leading the ML strategy for Search, Ranking, and Content AI. As a technical lead and pod architect on the Tripadvisor Experiences R&D team, you will evolve the core discovery engine for their travel experiences marketplace and formally mentor mid-level and associate ML scientists.

You'll work with PyTorch, distributed training, Docker/K8s/IaC, and Python backend. The company builds foundation models for extreme physics to accelerate progress in semiconductors, aerospace, defence, and fusion. Joining a small, research-heavy team, you'll be the first dedicated engineering owner for the ML stack.