AI Jobs in United Kingdom

View detail

Contributors may design rigorous energy engineering problems reflecting professional practice; evaluate AI solutions for correctness, assumptions, and constraints; validate calculations or simulations using Python (NumPy, Pandas, SciPy); improve AI reasoning to align with industry-standard logic; and apply structured scoring criteria to multi-step problems.

View detail

Contributors may design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python (NumPy, SciPy, Pandas), improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.

View detail

The job responsibilities include having industry experience as a research engineer in an AI-related company and being excited to work, learn, and teach within a collaborative team on challenging problems.

View detail

Senior AI Engineers at Inworld are responsible for researching, building, optimizing, and deploying production machine learning (ML) systems that thousands of developers integrate with their systems. Their work focuses on solving difficult research and engineering problems related to building the engine for the next generation of AI-driven software, with a primary focus on speech modeling including speech-to-text (STT) and text-to-speech (TTS). They address challenges unique to working with audio such as data collection, efficient training infrastructure, creating reinforcement learning alignment environments, and ultra-low latency inference optimizations.

View detail

As a Training Runtime: Process Management Engineer, you will design, build, and maintain software to orchestrate and monitor machine learning workloads on large supercomputers, working primarily with Python and Rust. Your responsibilities include profiling and optimizing the software stack to support computation orchestration at frontier scale, improving reliability, observability, and fault tolerance for long-running jobs, debugging complex distributed systems issues across large clusters, and responding to the changing shapes and needs of the ML systems to enable researchers. The role involves building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability, and working on software that ties thousands of computers together as a unified system while promoting a fast debugging and development cycle and relentless optimization for scale, stability, and performance.

View detail

Build systems that integrate with the EHRs used in American healthcare to make Heidi feel like a native capability rather than a plugin. Develop systems that simplify the complexity of US healthcare billing, compliance, and payer constraints so clinicians do not have to manage these complexities. Write clean, testable code with strong interfaces, error handling, and observability, ensuring the workflows are reliable for clinicians, operators, and downstream systems. Focus on outcomes by ensuring that the built systems help clinicians and improve practice revenue. Create agentic workflow functionalities where AI assists with extraction, reconciliation, and drafting within workflows, incorporating human review, auditability, and control. Collaborate closely in a team environment with frequent pairing and shared ownership of design and implementation. Learn about healthcare organizational operations, especially those serving US customers, to translate requirements and constraints into product improvements.

View detail

Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements. Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior. Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

View detail

Run technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast. Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more. Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale. Juggle up to 10 concurrent projects while feeding customer insights back to product and engineering.

View detail

Work closely with the Product Lead as a Mid-level or Senior Fullstack Engineer operating at the intersection of core product development and clinical application, building end-to-end AI features including architecting and shipping fullstack solutions from React frontends to Python backend services that leverage voice AI and LLMs to automate clinical workflows. Implement and fine-tune audio processing pipelines to ensure Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments. Translate complex clinician feedback into technical solutions, rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling. Optimize fullstack performance to handle real-time audio streaming and token generation to minimize latency and create seamless conversational experiences for clinicians. Partner with implementation and clinical teams to quickly ship critical integrations and feature requests from concept to production in days rather than quarters.

View detail

Build systems that integrate seamlessly with the EHRs used in American healthcare to feel like a native capability rather than a plugin. Develop systems that handle complex US healthcare billing rules, compliance requirements, and payer constraints so that clinicians do not have to manage these complexities. Write clean, testable code with strong interfaces, error handling, and observability for workflows depended on by clinicians and operators. Focus on outcomes that help clinicians and improve practice revenue, not just code functionality. Create AI-assisted workflow functionality that supports extraction, reconciliation, and drafting with human review, auditability, and clear controls. Collaborate closely with others through frequent pairing and shared design and implementation ownership. Learn about healthcare organizations' practical operations and US customer requirements to guide product improvements.