Top Tech Jobs & Startup Jobs in London

Design, develop, and maintain scalable Python backend systems and APIs. Lead end-to-end development, optimize performance, participate in architecture decisions, conduct code reviews, resolve production issues, and mentor junior engineers.

Design and build scalable Python backends and APIs, integrate and deploy LLM-powered applications (chatbots, summarization, semantic search), optimize model performance and costs, develop data pipelines for training and inference, ensure code quality and CI/CD, collaborate cross-functionally, and mentor junior engineers.

Expert reviewers will evaluate UK-law answers generated by two AI platforms. They will run identical prompts, compare outputs, score responses using a standardized rubric, and provide concise written feedback. The role requires at least two years of primarily law-firm experience in corporate, M&A, or transactional practice, UK qualification to practise, strong UK corporate and commercial law knowledge, fluent English, independence, and deadline management. The initial commitment is approximately 10 hours, with potential for additional work under an NDA.

Build and evaluate advanced Excel finance tasks for AI training data. Responsibilities include creating financial models and analyses, designing realistic finance scenarios, writing solutions, reviewing task accuracy, providing feedback, and collaborating with subject matter experts. The role requires advanced Excel skills, including formulas, PivotTables, dashboards, Power Query, Power Pivot, macros, and VBA, plus professional finance experience in areas such as private equity, investment banking, hedge funds, equity research, accounting, or FP&A.

Build and evaluate MLOps and ML systems tasks for frontier AI training data. Responsibilities include designing technical challenges, writing solutions and evaluation rubrics, profiling and optimizing GPU workloads, debugging distributed systems, improving model performance, and supporting high-throughput LLM inference. The role requires production experience with ML infrastructure, serving systems, GPU accelerators, JAX or PyTorch, and strong technical communication.

Design insurance pricing, reserving, forecasting, and portfolio-risk scenarios for AI model training. Create actuarial analyses and reference answers, evaluate AI outputs for quantitative and methodological accuracy, identify unsupported assumptions and errors, and provide structured feedback. The role requires explaining actuarial methods and business implications to technical and nontechnical audiences while participating in calibration and onboarding sessions.

Design reinsurance and program-business scenarios, assess AI-generated responses, create market-quality reference materials, and provide detailed feedback on treaty structures, delegated authority, fronting, captives, risk transfer, contract logic, financial responsibilities, and market realism.

Annotate Korean PDF pages by identifying, bounding, typing, and ordering document regions; link related components; transcribe Hangul, hanja, and handwriting exactly; capture page metadata; and flag illegible or unsuitable pages. Experienced annotators also review colleagues’ work. The role requires exceptional character-level accuracy, consistent taxonomy application, and comfort with complex layouts such as tables, diagrams, newspapers, exams, and handwritten forms.

Design complex insurance claim and coverage scenarios for AI model training, including disputed coverage, litigation, allocation, bad-faith risk, and major-loss settlement strategy. Produce senior-level claim analyses, authority requests, reserve rationales, and litigation plans; evaluate AI responses against claims standards; identify unsupported or improper positions; and provide written feedback. Participate in onboarding and calibration sessions.

Design and evaluate life insurance and annuity advisory, underwriting, policy-service, suitability, and replacement scenarios for AI training. Create expert reference responses, assess model outputs for product accuracy, mathematical correctness, suitability, tax treatment, and disclosure compliance, and provide feedback to improve model performance. Participate in onboarding and calibration sessions.