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

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.

You will work with C++, Java, Kotlin, TypeScript, front-end frameworks, APIs, machine learning, and agentic coding to build new products within Google Labs Science. Partnering with Google DeepMind, the team translates breakthrough GenAI research into user-centric products that accelerate scientific discovery.

Sonar★5.0 (2)· London

You will work with Python, core ML frameworks, and post-training techniques including GRPO, PPO, RLVR, SFT, PEFT, and preference/safety alignment (Rust or SonarQube flagship languages are a plus). You will join a cross-disciplinary team developing advanced products that post-train models to power enterprise agentic coding practices, ensuring code meets enterprise standards.

You will use Python, core ML frameworks, and post-training techniques (GRPO, PPO, RLVR, SFT, PEFT) to develop enterprise-grade coding agents. This cross-disciplinary team combines Sonar’s static analysis with LLM post-training to help customers build agents generating high-quality code meeting enterprise standards.

Sonar★5.0 (2)· London

Sonar seeks a senior researcher with an advanced degree and 4+ years of ML industry experience. The role involves developing enterprise-grade coding agents using Python, ML frameworks, and post-training techniques (e.g., RLVR, SFT) for Sonar’s AI code verification platform. You will work within a cross-disciplinary team to translate prototypes into products.

Work with Rust, Python, Java, Kotlin, C++ and related languages, building a next-generation software platform that integrates robotics, sensors and autonomous systems for demanding environments in the security sector.

Design and develop low-latency, high-throughput trading and market data systems using modern C++ (C++17/20) on Linux, with additional exposure to Python, Rust, Go, Java, or C#. The team handles strategy execution, market data processing, and core infrastructure on the direct trading path.

Google★4.3 (6.2k)· London

You will work with C++, Java, Kotlin, TypeScript, front-end frameworks, API development, machine learning, agentic coding, and GCP. This role is in Google Labs Science, which partners with DeepMind to transform GenAI research (e.g., Co-Scientist, AlphaEvolve) into products that accelerate scientific discovery.

You will engineer agentic AI decision loops, retrieval and embedding pipelines, and rigorous testing frameworks using Python, orchestration frameworks, vector databases, and semantic search, with JVM languages as a plus. Own the full model lifecycle, balancing fine-tuning specialized models versus frontier LLMs, while mentoring on production-grade ML standards. This is a senior ML engineering role for iForce Connect, building deep, integrated AI systems that navigate complex datasets.

Google★4.3 (6.2k)· London

Work with C++, Java, Kotlin, TypeScript, front-end frameworks, APIs, and GCP to design and build machine learning and agentic systems. As part of Google Labs Science, you will partner with Google DeepMind to transform GenAI research into products that accelerate scientific discovery.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

Design and deploy enterprise-grade AI applications using Python, LLMs (OpenAI, Claude, Gemini), RAG, vector databases, and LangChain/LangGraph on Azure/AWS with Docker and Kubernetes. Ascendion is an AI-first software engineering services provider delivering transformative solutions across multiple regions.

Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

Work with BigQuery, Airflow, BigTable, DynamoDB, Python, Scala, Spark, TensorFlow/PyTorch, Docker, Kubernetes, and LLMs building end-to-end ML pipelines. You'll own ML-powered features for the Recommendations Experience team, connecting 200M+ users with personalized music.

The Head of Technology will work hands on with Python and SQL (C#/Java beneficial) to build out the hedge fund's internal platform, covering trading and portfolio data flows, analytics and risk applications, research tooling, and operational systems. This role leads the technology function from the ground up, with scope to build a team as the fund scales.

You will work with Python, SQL, R, MATLAB, C++, Java, Oracle, Postgres, Snowflake, and Git. The Global Quantitative Research Group designs, implements, and supports margin, stress testing, and risk models for clearing houses across interest rate, equity, credit, and commodity derivatives.

You will work with Python, JavaScript/TypeScript, AWS/GCP/Azure, LLM APIs (OpenAI/Anthropic), RAG, embeddings, vector databases, and SQL to build and deploy production-grade AI systems for equity research, automating screening, idea generation, and building internal APIs and UIs for an investment team.

Design and develop AI projects using Python, Java, TypeScript, Go, REST APIs, and databases. The team builds and deploys the full lifecycle of generative AI applications for customers, including RAG, agents, and fine-tuning. No team size is stated.

You will build and maintain production-grade software systems for AI training, evaluation, and deployment pipelines using Python, TypeScript, or other modern languages. You’ll design APIs, data pipelines, and backend services, working with cloud platforms (AWS, GCP, Azure), containerized environments, and CI/CD workflows. The company builds the infrastructure that powers AI products used by millions worldwide.

Use Python, Kotlin/Java, SQL, Airflow, Kubeflow, MLflow, and containers to build the ML lifecycle platform for financial crime detection at Wise, designing training pipelines, model serving, evaluation, and monitoring to enable data scientists to scale detection reliably.

Google★4.3 (6.2k)· London

Manage engineers building Google’s Learning Platforms within the Global Business Organization, which powers Google’s ecosystem of products and services for customers and partners. Work with back-end languages (Java, Python, Golang, C++) and front-end (JavaScript, TypeScript, HTML, CSS), plus ML model fine-tuning and evaluation.

Infosys★3.8 (17k)· London

Work with LLMs, RAG, agentic AI, MCP, LangChain, LangGraph, LlamaIndex, Semantic Kernel, vector databases (Pinecone, Weaviate, Chroma), cloud platforms (Azure, AWS, GCP), and MLOps tools (Docker, Kubernetes, FastAPI). As a Generative AI Consultant at Infosys, you will drive the design and implementation of innovative AI solutions for clients.

You will work with AWS (EC2, ECS, Lambda, DynamoDB), Kubernetes, Terraform/CloudFormation, Python/Go/Java/C#, Bash/PowerShell, Docker, Grafana (Loki, Mimir, Tempo), Prometheus, ELK, Splunk, Datadog, and CI/CD tools like Jenkins or GitLab CI/CD. The team delivers enterprise software for cloud and on-premises environments to enhance customer experiences, maintain compliance, and fight fraud, with your role focused on overseeing production system availability, automation, and reliability. No team size is specified.

You will work with Python, Java, Azure, LLMs, vector DBs, RAG, and frameworks like LangChain, Haystack, Hugging Face, and Crew AI. The AI organization builds and deploys scalable, production-grade AI-powered applications for business value within the oil and energy/HR technology sector.