Top Research Jobs in London

As a Sector Analyst for European Equities, you will analyze alternative data, produce research, and support investment professionals in their decision-making processes.

Design, build, and operate large-scale RL post-training systems for multimodal foundation models: distributed training, high-throughput rollout generation, environment and reward infrastructure, evaluation and debugging tooling, and efficiency/stability improvements. Collaborate with researchers to productionize RL methods and run stable RL training across thousands of GPUs.

Design, train, and deploy state-of-the-art, highly efficient computer vision and multimodal LLM models for low-power edge devices. Improve training algorithms, data pipelines, model architectures, and deployment tooling to ship AI features to millions of cameras. Prototype demos and optimize cloud and on-device inference.

Build and optimize state-of-the-art, resource-efficient deep learning models and multimodal LLM features for deployment on low-power embedded devices. Improve training algorithms, data pipelines, model architectures, and training infrastructure (cloud and edge), and ship models to production at scale using Kubernetes, GCP, and auto-labeling workflows.

Drive sales growth across Europe by acquiring new clients and expanding existing accounts for syndicated research, custom research, and consulting services. Qualify inbound leads, align client needs with ABI Research solutions, build client relationships, collaborate with analysts and internal teams, and represent the company at industry events.

Join the Pretraining team to design and implement model architectures, optimizers, and data pipelines; run and analyze experiments; scale and optimize training infrastructure; and develop tooling across the stack to advance large language model research and production.

The Lead Research Engineer will provide technical leadership, develop scalable ML solutions, and collaborate with teams to innovate and deliver products that enhance customer experiences in legal, accounting, and government sectors.

Qube Research & Technologies offers travel grants to support Master, PhD, and Postdoc students attending NeurIPS 2026. Applicants submit a CV and details of any NeurIPS submission; selections prioritize presenters. Successful recipients receive travel, accommodation, a daily stipend, and an all-access conference pass. Applications reviewed by QRT; deadline October 2, 2026.

Design and implement IAM solutions and scalable systems, collaborate with stakeholders, mentor junior engineers, and manage CI/CD pipelines.

Analyze market risks through VaR and stress testing, enhancing risk reporting, and collaborating with trading and risk teams.

Lead and execute laboratory, phantom, benchtop, and in-vivo experiments for non-invasive optical neuromonitoring. Own experimental workstreams from protocol design to analysis and reporting, develop and validate tissue-mimicking phantoms, acquire physiological optical data, troubleshoot systems, generate datasets to support product development and ML, and communicate findings to cross-functional teams while mentoring junior staff.

As a Data Scientist at QRT, you will work with data to inform trading decisions, prototype data handling code, and solve data related problems.

Develop, maintain and modernize trading systems across multiple asset classes. Diagnose production issues, improve performance and reliability, contribute to architecture of a replacement platform, and collaborate with traders and stakeholders to deliver stable, high-performance solutions.

Join Verve as an Insight Associate, focusing on AI-powered market research. Learn to design research, interpret human behavior, and contribute to client projects using AI tools.

Conduct empirical research into AI "scheming": design and run RL experiments on LLMs, build model organisms, develop scalable evaluation techniques, study scaling laws and AI cognition, and collaborate with partner labs to influence deployment and mitigation strategies.

Design, run, and automate pre-deployment evaluations of frontier AI models. Analyze large model transcripts to surface behaviors, build scalable evals, collaborate with AI labs, and improve evaluation pipelines and tooling.

Research, prototype, and deploy ML models for physiological sensing (radar, audio, other signals). Design experiments, implement production-grade models for cloud and on-device inference, optimize for constrained compute, collaborate with clinical and engineering teams, and contribute documentation and regulatory evidence.

Develop systems that enhance high-performance trading platforms, focusing on workload distribution and real-time support for quantitative researchers.

As a Performance Engineering Manager, you'll lead the Compute Performance Engineering team, optimizing large-scale workloads across Linux HPC and Kubernetes. Responsibilities include strategy development, team leadership, profiling workloads, and enhancing compute infrastructure for better performance.

Work within the Data Analytics team to drive data-driven decision making: lead analytics projects, model and simulate business problems, produce end-to-end reporting, visualise insights for technical and non-technical stakeholders, provide technical oversight and mentor colleagues.

Lead end-to-end qualitative research projects for FMCG clients: manage project teams, client relationships, deliver discussion guides and reports, ensure quality, profitability, and contribute to business development. Hybrid role with occasional domestic UK travel and focus on brand, communications, product testing and consumer insight.

The Technology Research Analyst will conduct research on technologies, author reports, engage with stakeholders, and support business development activities.

The role involves converting Python research models into C++ for high-performance trading systems, backtesting, and collaborating with research teams to enhance trading strategies.

Role involves monetising alpha through execution strategies in futures markets, developing execution logic, collaborating on research, and monitoring strategies' performance.

Design, build, and productionise large-scale optimisation models and bespoke solvers for last-mile scheduling, assignment and pricing. Translate operational requirements into mathematical programming and heuristic solutions, benchmark and monitor performance, and work cross-functionally with engineering and analytics to deploy and evolve automated decision systems.