Top Machine Learning Jobs in Belfast

Lead engineering projects in data acquisition, curate multimodal datasets, develop scalable data pipelines, and conduct experiments for insights in AI.

The Enterprise Account Executive will drive new client acquisition, develop sales pipelines, and close business deals by partnering with clients and understanding their needs.

As a Software Engineer Intern, you will build features for user-facing products, design data pipelines, implement scalable services, and contribute to technical documentation while being part of a collaborative team.

The Technical Product Manager leads product discovery, collaborates with stakeholders, and manages the product lifecycle focusing on AI-driven solutions and digital products.

As Workforce Planning Lead, you will manage global delivery operations, optimize resource allocation, and drive process improvements while leading a high-performing team.

Lead the product strategy and development of AI-powered cybersecurity products. Collaborate with engineering, sales, and marketing teams to drive product success and market adoption.

Lead the development and deployment of AI and ML solutions, oversee MLOps strategy, and collaborate with data scientists to enhance data-driven products.

The Applied Machine Learning Scientist will innovate and implement ML algorithms to enhance advertising performance, collaborate with engineers, and prototype in data-driven models.

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

The internship involves research and development in AI and NLP, focusing on semantic systems, embedding-based retrieval, and collaboration on publishable research.

The Research Lead will oversee AI climate and weather modelling research, coordinate a team, engage with partners, and ensure impactful research outputs.

The Staff/Senior Backend Engineer will bridge Quant Analysts and engineering teams, implement production-grade models, and enhance architecture and best practices.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

As a Staff Machine Learning Engineer, you will lead cross-team ML projects, mentor engineers, and develop solutions aligning with business goals by utilizing advanced ML techniques.

The Senior Machine Learning Scientist will design and build AI products, applying advanced ML techniques to transform data into actionable insights, leading cross-functional collaborations.

Lead the design, optimization, and deployment of machine learning forecasting algorithms and models that support Gorilla’s energy platform, ensuring scalability and integration while mentoring peers.

As a Senior Software Engineer, you'll create advanced AI systems to improve developer productivity, integrate existing tools, and mentor junior engineers.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

As a Senior Data Engineer, you'll design scalable data pipelines, collaborate with engineers and product teams, and evolve the architecture to support growth in users and data.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

The Machine Learning Platform Engineer will manage cloud infrastructure, support AI researchers, and deploy models in production, focusing on MLOps and CI/CD practices.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

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.

Research and develop machine learning models for cybersecurity applications, integrating outcomes into products and collaborating with engineers.