Top Machine Learning Jobs in Bristol

As a Machine Learning Engineer, you will deploy AI/ML systems, translate client needs into solutions, and engage with users to provide support and improvements.

Develop the machine learning compiler stack for Fractile's AI acceleration hardware, ensuring performance of language models through collaboration with hardware and ML engineers.

As a Senior ML Runtime Engineer at Fractile, you will integrate AI acceleration hardware with ML software projects, develop high-performance runtimes, and collaborate on co-design methodologies.

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

Join Starling as a Software Engineer to design, implement, and maintain ML-powered features, collaborating with engineers and data scientists, while delivering impactful solutions in a hybrid working environment.

Lead end-to-end ML initiatives: integrate and fine-tune models, optimize GPU inference for latency and throughput, build evaluation and monitoring tooling, collaborate on scalable serving systems, and mentor engineers.

The VP of Research, Machine Learning will lead the research direction for AI systems, focusing on intelligence design, evaluation frameworks, and advanced machine learning techniques while ensuring real-world applicability.

The Staff Machine Learning Engineer will lead the execution of ML systems, ensuring reliability and scalability while collaborating with cross-functional teams to deliver high-quality AI solutions.

The Senior Machine Learning Engineer will build core ML systems, handle data preparation and iteration, debug model issues, and ensure reliable production performance while mentoring other engineers.

As Technical Lead, you'll own ML system execution, manage data pipelines, model deployment, and ensure performance under real-world conditions while collaborating with the team.

The role involves building end-to-end production-grade ML systems, optimizing pipelines, integrating models into applications, and maintaining data systems.

As an AI/ML Engineer, you will design and develop AI-powered applications, integrate AI features into BPM systems, and collaborate with teams to improve operational efficiency through innovative AI solutions.

The Senior Machine Learning Engineer will design, build, deploy AI solutions, collaborating with cross-functional teams and ensuring maintainability and scalability of ML systems.

The Senior Machine Learning Engineer will develop machine learning solutions for online gaming platforms, improving security and user experience through data-driven decisions, while collaborating cross-functionally.

Lead a team of Senior ML Scientists to enhance automated decision-making in credit risk modeling, optimize data applications, and collaborate across departments.

As a Senior Machine Learning Scientist, you'll improve customer outcomes through automated decisioning using ML and statistical modeling, focusing on credit risk modeling and collaborating with cross-functional teams.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Lead Machine Learning Engineer, you'll set technical directions for AI projects, design scalable ML systems, lead project delivery, and mentor a team of engineers while collaborating with clients to achieve their goals.

Design and optimize ML/AI pipelines using Azure Databricks, implement CI/CD pipelines, and ensure compliance in AI solutions.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.