Top Machine Learning Jobs in Bristol

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

As Senior Product Manager, you'll lead the integration of global airline partners, optimize supply metrics, and enhance product specifications for seamless booking automation, focusing on AI solutions and API performance.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

As an MLOps Engineer, you will develop and implement ML features for pricing strategies, maintain MLOps practices, and ensure the performance and reliability of ML systems.

As an MLOps Engineer, you'll build and implement features enhancing data-driven pricing for hotels, ensuring reliability and scalability of ML systems, streamline data pipelines, and collaborate with teams for impactful revenue growth.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

Lead the curriculum product strategy and a team of Product Managers, retain hands-on ownership of high-impact products, collaborate with cross-functional teams, and drive AI/data-driven product development and adoption through the full product lifecycle.

As a Principal Engineer at M&S, you'll drive technical strategy, influence architecture, and mentor engineers while delivering on personalization, search, and machine learning features in collaboration with cross-functional teams.

The Senior ML Data Engineer will enhance data workflows, collaborate with teams to build datasets, influence data strategies, and implement pipelines for effective data usage in AI/ML products.

As a Staff Machine Learning Engineer, you will lead the development of complex ML systems and MLOps pipelines, mentor junior engineers, and ensure scalable and reliable solutions for retail workflows.

As a Data Analyst III, you will analyze data, create visualizations, and provide insights using AI tools to support business decisions while collaborating with stakeholders.

Lead clinical studies by providing statistical support, employing advanced analytical methods, and collaborating with cross-functional teams to optimize clinical development processes.

Build and operate backend ML platform services for context retrieval, compression, and evaluation to power AI assistants. Own architecture, implementation, observability, and reliability while enabling other teams to integrate reusable APIs and tooling.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

As a Staff/Principal Machine Learning Engineer, you will optimize and scale multimodal inference systems, ensuring high performance and reliability in production environments.

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.