Top Machine Learning Jobs in Belfast

Lead applied AI research and architecture for GenAI in cybersecurity: design LLM architectures, implement production-grade deep learning systems at scale, mentor scientists, set technical standards, and align AI strategy with business goals.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

Lead and grow a distributed engineering organization building customer-facing security capabilities: proprietary scanners, AI/ML detection engines, agentic remediation, vulnerability management, and security foundations. Set vision and roadmap, drive architecture and delivery, partner with product management, establish engineering standards, and represent the group in cross-functional and customer forums.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

Lead and rebuild FP&A at Napier: own budgeting, forecasting, and long‑range planning; implement AI-native forecasting and automation; deliver performance reporting and commercial insights; partner with senior stakeholders across functions; support M&A and transaction readiness; and improve finance systems, controls, and reporting cadence to enable growth.

Lead delivery of FX trading platform initiatives within an Agile feature team: manage projects and roadmaps, maintain RAID logs and backlogs, chair stakeholder and steering committee meetings, produce presentations and minutes, prioritize requirements, and drive resolution of risks and dependencies to deliver high-quality, strategic technology solutions for FX trading.

Perform and oversee balance sheet exception reporting and controls, produce BSER and management dashboards, investigate and resolve reporting exceptions, analyze trends, and partner with Operations, Finance, Risk and Technology to improve controls and data quality. Maintain documentation and support ad-hoc and regulatory reporting requests.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and manage an ML engineering team building post-origination credit models for repayment, collections, recovery, and loss mitigation. Define technical strategy, design and scale ML solutions, partner with product, engineering and risk, mentor engineers, and operationalize models to minimize loan loss and personalize collections.

Join the quantitative credit strategists team to develop analytics solutions for credit trading, collaborating closely with trading desks to enhance decision-making.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Lead the development and optimization of machine learning algorithms, owning the end-to-end model development and collaborating with Data Engineers for integration into live systems.

The role involves designing scalable data pipelines, implementing custom ML algorithms, and working on microservice architectures for ad optimization models.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

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.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

Lead development of enterprise commercial intelligence: build data models (pipeline, forecasting, segmentation), deploy AI/ML for forecasting and churn, create dashboards, establish data governance, partner with senior leaders to drive insight-led decisions and adoption across global teams.

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

Lead statistical planning and delivery for clinical studies using R and RShiny, mentor biostatistics staff, prepare SAPs and programming specifications, perform quality control, support submissions and regulatory interactions, and develop/maintain R-based visualization apps and infrastructure.

Drive end-to-end product design for Avid Content Core, representing the customer to define and prioritize product stories, collaborate with engineering on implementation, integrate AI into SaaS offerings, engage customers and partners, and ensure workflows, deployment, security, and quality throughout the agile development lifecycle.

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

Lead market pricing for the UK pet insurance book: develop demand, elasticity, and price-optimisation models, monitor competitors and market trends, make rate recommendations, present findings to stakeholders, support pricing strategy, and line-manage one pricing analyst.