Top Machine Learning Jobs in Bristol

The Head of AI will lead the AI strategy for Kainos, focusing on product innovation and integration of AI solutions across its product suite. This involves collaborating with various teams, mentoring staff, and ensuring technical excellence in the development of AI-driven features while maintaining ethical standards. The role requires a strategic thinker with strong leadership skills and a robust background in machine learning and AI technologies.

The Cloud Software Engineer will integrate new AI accelerator hardware into Kubernetes environments, focusing on MLOps technologies such as Kubeflow, Volcano, and Kueue. Responsibilities include developing Go applications, ensuring seamless hardware integration, participating in code reviews, maintaining software quality, and writing documentation.

As a Machine Learning Engineer at Graphcore, you will develop and optimize AI models for specialized hardware, collaborate with teams on AI applications, and engage with the AI community to innovate in the application of AI technology. Responsibilities include implementing machine learning models, conducting experiments, and improving model efficiency.

The Enterprise Solutions Engineer will leverage their expertise in AI and Machine Learning to assist large organizations in realizing their Generative AI ambitions using Stability AI's products. Responsibilities include engaging with technical stakeholders, delivering technical demonstrations, and collaborating with product and research teams to develop solutions that meet customer needs.

The Senior AI/ML Engineer will design and implement AI/ML models to analyze blockchain data, collaborate with teams to integrate these models into Nansen's platform, mentor junior engineers, and apply innovative solutions to drive decision-making for crypto investors.

As a ML Engineer, you will create and implement features to enhance revenue management for lodging customers. You'll develop machine learning models, analyze data to identify trends, and collaborate with various teams to optimize product features and pricing strategies.

As a Machine Learning Performance Engineer at Autodesk Research, you will optimize machine learning tasks, implement GPU kernels, and collaborate with researchers to enhance ML-powered features. Key responsibilities include profiling, optimizing code, and utilizing GPU resources effectively while documenting processes and presenting findings.

As a Machine Learning Cloud Optimization Engineer, you will enhance ML-powered product features, optimize code for machine learning tasks, and collaborate on projects involving AI technologies. Responsibilities include training models, processing data, and presenting results to teams while working remotely or in a hybrid setting.

As a Machine Learning Performance Engineer at Autodesk, you will implement GPU kernels, optimize machine learning tasks, and collaborate on projects with researchers. Your responsibilities include writing efficient code for machine learning, managing GPU resources, and supporting research through ML pipelines and prototypes.

As a Machine Learning Cloud Optimization Engineer at Autodesk, you will enhance ML product features, optimize tasks, implement generative AI features, and collaborate with a global team to support research through the construction of ML pipelines and prototypes.

As a Senior Machine Learning Engineer, you will design, develop, and deploy advanced machine learning models for CoachHub's core data products. Responsibilities include data preparation, model optimization, performance monitoring, and collaboration with stakeholders.

The Senior ML Data Engineer will collaborate with product managers and data scientists to develop end-to-end machine learning solutions, maintain a serverless ML-powered GraphQL stack, support deployment of ML models, and manage large datasets effectively while ensuring operational infrastructure is supported.

As an Engineering Manager, you will lead multiple product teams to enhance vegetation modeling and data ingestion, manage up to 10 engineers, and ensure high-quality product delivery while fostering team growth and collaboration.

The Engineering Manager will lead a cross-functional team responsible for core translation systems, drive the technical roadmap aligned with business goals, mentor team members, establish software development best practices, and provide technical leadership in AI/ML development to enhance product offerings.

As a Senior Machine Learning Engineer on the ShelfView team, you will focus on enhancing product feature sets and improving computer vision algorithms for real-time shelf recognition. Responsibilities include end-to-end quality improvement, mentoring colleagues, and utilizing the latest research in detection and segmentation.

The AI/ML Specialist Solutions Architect at Nebius designs scalable AI solutions for clients, resolves technical challenges, and manages large-scale AI deployments utilizing Nebius services. Responsibilities include building customer relationships, delivering technical presentations, and collaborating with engineering teams.

The Senior Machine Learning Engineer will lead the development of machine learning models and algorithms for detecting account takeovers, collaborate with teams to implement solutions, monitor production models, and mentor junior members.