You'll work with Python, FastAPI, TypeScript, React, and GCP to build services, data models, and APIs for a behavioral simulation platform that creates "digital twins" of populations. The team of 17 at Electric Twin is building this platform to help organizations predict human behavior with 95% accuracy.

You will use PyTorch or JAX, Python, and DFT packages like VASP or Quantum Espresso to develop machine learning interatomic potentials (MLIPs) that accelerate discovery of advanced functional materials by integrating ML with first-principles physics and automated experimental data.

You will design and train custom deep-learning models and fine-tune large language models using Python, TensorFlow, or PyTorch. The work involves leading research for Kangal AI, a venture building frontier AI for governments and security clients. You will own the entire model stack and scale a research team as a founding hire.

You'll work with Python, reproducible/containerized pipelines, cheminformatics representations (SMILES, InChIKey, fingerprints), and computational mass spectrometry. Novogaia is an applied AI drug discovery company building foundation models for molecular structure prediction from mass spectrometry data, and you'll own the design of internal benchmarks and evaluation pipelines for these models.

Glasswall★0.0· London

Work with Python, PyTorch, Scikit-learn, Hugging Face, Git, CI/CD, and MLOps tools to build, tune, and optimize machine learning, deep learning, and generative AI models. You will design LLM-powered systems (RAG pipelines, fine-tuning, agentic AI architectures) and production-grade pipelines within the Applied AI team at Glasswall. This hands-on role includes providing technical guidance and mentoring to mid-level and junior engineers.

Fitch Group★4.5 (4)· London

You’ll work with Kubernetes, Docker, AWS, Azure, Datadog, GitHub Actions CI/CD, AWS Bedrock/SageMaker, and script in Python, PowerShell, or Bash. The role embeds within Fitch

Millennium Management★3.8 (21)· London

Work with Python, C++, Docker, Kubernetes, Ceph, MongoDB, Kafka, Numpy, Polars, Scikitlearn, and Pytorch on a small, collaborative systematic trading team. The role involves developing real-time event-driven systems for alpha research, feature engineering, portfolio construction, and trade execution.

Luxoft★4.5 (669)· London

Lead the architecture of production-grade LLM orchestration and multi-agent systems using LangGraph or LangChain, working with Python (asyncio, FastAPI), TypeScript (Next.js/React), AWS (ECS Fargate, Lambda, SQS, Aurora, Neptune), and AWS CDK or Terraform. The team is developing an Agentic AI solution to generate investment insights from sales and research materials for client meetings.

You'll work with Go, Python, Rust, AWS/GCP/Azure, Docker, and Kubernetes to build backend services and APIs for the Training & Experimentation team. This team develops the platform that enables developers to experiment at scale, train models, and launch distributed training jobs.

Smart Bricks is hiring a Head of Applied AI to build an Applied AI Lab that deploys AI solutions for large real estate organizations. You will work daily with enterprise customers, hiring and leading a team of Forward Deployed Engineers, AI Engineers, Solutions Architects, Applied AI Consultants, and Deployment Managers. The role spans AI/ML, software engineering, and product collaboration to convert customer work into platform capabilities.

You'll work with Python, NLP/LLMs, AI/ML, cloud infrastructure, SQL/no-SQL, and optionally C++/Rust. Catapult builds personalised AI models that understand your full work context across email, calendar, Slack, Notion, and Google Docs. As a founding engineer, you'll own retrieval and reasoning systems end-to-end from research to product.

You will work with Python, TensorFlow or PyTorch, and large language models, building custom deep-learning models and training/fine-tuning LLMs on a proprietary dataset. Kangal AI builds frontier AI for governments, national security, and private corporations. As a founding hire, you will own the model stack and scale the research into a team you lead.

Work with Python, containerized pipelines, and cheminformatics representations (SMILES, InChIKey, molecular fingerprints) to build ML evaluation benchmarks for molecular structure prediction from mass spectrometry data. You will design adversarial checks, leakage-safe datasets, and repeatable pipelines that measure model quality for an applied AI drug discovery company.

Work with Python, PyTorch, Scikit-learn, Hugging Face, MLFlow, AzureML, and CI/CD/MLOps tools like Azure DevOps, Docker, and Kubernetes. The Applied AI team builds production LLM-powered systems, agentic AI, and ML pipelines for Glasswall’s cybersecurity solutions. No team size is stated.

Work with C++ and Python on multithreaded, real-time trading infrastructure. You will develop ultra-low-latency exchange protocol encoders and fine-tune fully automated trading strategies for a data-driven prop fund. The role is in a small, fast-paced team that collaborates with researchers and operations.

They will use Python, LLM tooling (prompting, RAG, agents, MCP, fine-tuning, evaluation), and AI platforms/APIs. Working on PIMCO's Tactical AI Automations team, they deploy AI assistants and agentic workflows across Portfolio Management and Analytics, and support Lane Assist/

You'll lead a 6-7 person team owning core ML infrastructure—distributed model training, LLM hosting/fine-tuning, and scalable deployment—using Python heavily with working C++/Java, at a top systematic quant fund. This hands-on engineering manager role drives ML into high-stakes production systems.

Architect low-latency inference pipelines for multimodal LLMs, TTS, and Vision models using Python, C/C++, PyTorch/JAX, TensorRT/ONNX, and custom CUDA/Triton kernels. Optimize with Speculative Decoding and KV-Cache quantization. Iconic Interactive is a seed-stage AI-native video game studio building intelligent virtual actors that speak, move, and react in real-time.

You'll work with LLMs, chain-of-thought prompting, RAG architectures, multi-agent tool use, Python, and FastAPI. Electric Twin builds synthetic populations for behavioral prediction, simulating human responses for global brands using LLMs.

You will develop and deploy production-grade LLM-powered agentic systems with persistent memory, tool orchestration, and RAG pipelines, integrating with Google Ads, Meta, and CRMs. You will build autonomous agents for marketing operations at a Series A startup building an AI-native teammate for marketing teams. As the second ML hire, you will shape the production stack and product roadmap.

Wells Fargo★3.6 (48k)· London

You'll work with Python, SQL, cloud and DevOps practices, AI/ML and Large Language Models, plus Axiom ControllerView on the Enterprise Functions Technology team. The role enhances and supports regulatory reporting platforms used by Wells Fargo's Finance Controllers organization.

Canva★4.3 (32)· London

You'll work with Python, PyTorch, vision-language models (Gemma, Qwen-VL, SmolVLM, MiniCPM-V), optimization techniques (quantization, pruning, distillation, hardware-specific compilation, task-specific fine-tuning), and on-device runtimes (Core ML, LiteRT/TFLite, ONNX Runtime, ExecuTorch). The Video Storytelling team builds models and systems behind Canva’s video AI, partnering with the Edge AI group to explore on-device deployment. This internship optimizes a video-capable VLM for on-device intelligent captioning on consumer phones.

Founding AI Research Engineer role building a proactive AI assistant that maintains a living model of a user’s entire digital workspace. Work on retrieval systems, knowledge bases, and reasoning models for live screen context. Own the full lifecycle from hypothesis to production. Requires 5+ years in NLP/LLMs, end-to-end project delivery, and strong Python, cloud, and database skills. In-person in Elephant and Castle, London.

You’ll use Python (C++/Rust a plus) for market-impact research, transaction-cost analysis, causal inference, and execution strategy. The team builds predictive models, runs A/B experiments, and produces analytics, simulations, and dashboards that traders and PMs use daily at a systematic fund developing its mid-frequency platform.

You'll own the ML stack using PyTorch, Docker, Kubernetes, and IaC, building distributed training and backend delivery for foundation models tackling extreme physics (semiconductors, aerospace, fusion). You join a small, research-heavy team as its first dedicated engineering owner, setting culture and owning model code, training workflows, and experiment infrastructure.