Top Machine Learning Jobs in Bristol

The Senior Solutions Engineer will work with large organizations to implement Stability AI's products in generative AI. Key responsibilities include assessing customer needs, providing technical guidance, delivering proof of concept demonstrations, and collaborating with product teams to enhance offerings based on customer feedback. Strong engagement with senior technical stakeholders is critical.

The Machine Learning Engineer will develop machine learning models and pipelines, research linguistic characteristics, engineer prompts for LLMs, and collaborate with teams to integrate AI/ML features into Smartling's platform, ensuring high-quality features for clients.

The Senior ML Engineer will design and optimize ML/DL solutions for unstructured content understanding and AI deployments, focusing on innovation and efficient architectures.

The Senior Software Engineer will discuss and research features, write code and documentation, and engage with the community on platforms like GitHub and Discord. Strong Python skills and excellent communication are essential.

As a Senior ML Engineer at Smartcat, you will enhance translation capabilities by optimizing machine learning models and managing the full lifecycle of ML projects. Responsibilities include developing benchmarks, improving translation quality, and automating systems while leveraging advanced technologies and cloud infrastructure.

Lead the development and optimization of machine learning models for image generation, focusing on latent diffusion and cloud scalability, while mentoring junior engineers and collaborating with cross-functional teams to enhance user experience.

As a Senior Backend Engineer, design and maintain APIs and data-stores while ensuring high-quality software standards and collaboration with product and frontend teams.

As a Machine Learning Engineer at Graphcore, you will develop and optimize AI models for specialized hardware. Collaborate with cross-functional teams, benchmark models, conduct experiments, and engage with the AI community to innovate AI technology.

Join Kayzen as a Senior Machine Learning Engineer, leading the development and deployment of big data machine learning models while collaborating closely with data scientists to drive innovation in AdTech.

As a software engineer, you'll develop end-to-end data analytics and ML solutions, working with open-source tools and collaborating remotely with global teams.

Develop and apply reinforcement learning algorithms to improve campaign performance. Work with engineering for platform enhancement and monitor implementations closely. Collaborate on product strategy and contribute to research efforts.

As a Senior ML Engineer, you will develop and deploy ML features for a CRM platform, collaborate with teams, and improve existing systems while iterating on user feedback.

The Machine Learning Engineer will develop AI-driven systems focused on linguistics, enhance translation systems using NLP and GenAI, manage the ML lifecycle, and ensure high-quality translations using linguistic metrics.

The Data Engineer will analyze source data, design and implement streaming data pipelines, develop and maintain batch processing pipelines, and collaborate with other professionals to manage feature life cycles and ensure data quality.

As a Senior AI/ML Engineer at Nansen, you will develop and monitor AI models to analyze blockchain data, collaborate with cross-functional teams to enhance the platform's analytical capabilities, and mentor junior engineers. Your work will significantly influence decision-making for crypto investors and drive the technology forward.

The Senior Machine Learning Engineer at Sona will lead the development of forecasting models to enhance client satisfaction and operational efficiency. This role involves solving complex problems, working with data, deploying machine learning systems, and engaging with industry experts to optimize model performance across various environments.

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.