Top Machine Learning Jobs in Belfast

Manage and expand strategic partner alliances for SailPoint’s enterprise software business. Develop joint business, marketing, technical certification, and go-to-market plans; generate partner-sourced pipeline; coordinate account mapping, co-selling, enablement, promotions, and implementation capacity. Serve as the primary liaison between SailPoint and partner organizations, monitor performance and KPIs, ensure compliance and delivery quality, and present quarterly business assessments. The role requires extensive enterprise partner-management experience, analytical skills, executive communication, and approximately 50% travel.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Manage a team of machine learning engineers developing credit and lending models for international markets. Set technical strategy, guide advanced ML solutions, partner with product, engineering, analytics, design, and risk teams, and ensure scalable underwriting capabilities. Provide hands-on technical leadership, clarify complex problems, manage trade-offs, and mentor engineers while contributing to Affirm’s long-term machine learning strategy.

Develop reusable automation, reliability frameworks, recovery utilities, and internal tooling for enterprise SRE teams. Review production readiness, reduce toil, improve monitoring and incident resolution, and promote reliability standards across hybrid cloud, on-premises, and containerized platforms. Collaborate with developers and SREs on architecture, CI/CD, telemetry, capacity planning, and production support. The role also requires foundational AI/ML knowledge, cloud experience, scripting skills, and strong communication.

Develop reusable automation, tooling, and reliability frameworks for enterprise SRE teams. Automate operational toil using scripting languages, review production readiness, support cloud and containerized platforms, improve monitoring and telemetry, and promote reliability standards across services. The role also involves backlog management, incident and problem resolution, CI/CD integration, capacity planning, and collaboration with developers and production engineers.

Manage and modernize hybrid database infrastructure supporting Citi’s finance applications. Responsibilities include migrating Oracle, MongoDB, and Big Data systems to AWS, Google Cloud Platform, and Snowflake; implementing AI-driven monitoring, performance tuning, and self-healing; managing high availability, disaster recovery, security, and compliance; and automating database administration through Python, Terraform, Ansible, and shell scripting across on-premises, OpenShift, and cloud environments.

Leads enterprise stability governance for Citi’s global Production Management organization. Owns stability metrics, KPI and SLO frameworks, executive reporting, data analysis, risk mitigation, application improvement programs, and governance of critical stability artifacts. Drives AI-enabled automation, operational excellence, and cross-functional preventative initiatives while managing team priorities, senior stakeholders, escalations, and mentoring engineers and analysts.

Own the Optimize Spend product backlog and delivery pipeline, translating roadmap priorities and stakeholder needs into user stories, acceptance criteria, and actionable increments. Coordinate sprint ceremonies, dependencies, risks, UAT, releases, and customer feedback across Product, Engineering, QA, and commercial teams. Support AI-powered features, integrations, invoice workflows, reporting, APIs, launch communications, training, packaging, and adoption planning.

Ten-week technology internship supporting TD Securities through software engineering, data platforms, analytics, automation, and applied AI work. Interns will design, build, test, debug, deploy, and improve applications and services while collaborating with engineers, data specialists, product partners, and business teams globally. The role provides structured technical training, mentoring, and exposure to technology challenges in financial markets.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Lead strategic relationships with Capital Markets organizations across EMEA, driving adoption of NVIDIA AI and accelerated computing solutions. Serve as the primary client contact, grow revenue and platform usage, develop account strategies, forecast business, and engage senior technology leaders. Collaborate with solution architects, business development, developer relations, cloud partners, hardware providers, and software developers. Communicate solution value, provide thought leadership, and travel to meet clients and partners.

Software engineering intern supporting the Platform Engines group and Policy Engine for SailPoint’s cloud identity security platform. Responsibilities include developing software, procedures, and test solutions; collaborating with software and QA engineers, technical writers, and product managers; and working in Agile teams. The intern will gain exposure to cloud and software technologies including Golang, Angular, AWS, Docker, Kafka, Kubernetes, REST, SQL, and Temporal.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with sales on complex opportunities, translate technical capabilities into business value, create reusable technical content, represent customer feedback to product teams, and coordinate cross-functional handoffs through implementation. Manage multiple concurrent sales cycles while supporting pipeline growth, deal expansion, and faster closes.

Lead technical pre-sales engagements for enterprise email security customers. Partner with sales teams, conduct workshops and presentations, architect tailored solutions, and guide migrations from legacy Secure Email Gateways to Abnormal AI’s API-based platform. Build trusted customer relationships, troubleshoot migration challenges, provide product feedback, develop enablement content, and represent the company at industry events.

Provides customer-facing threat analysis and fraud prevention expertise for behavioral biometrics solutions. Responsibilities include advising financial institutions, analyzing fraud detection performance, deploying rules for attacks, supporting data science research into emerging threats, delivering reporting and insights, educating customers, leading workshops, and contributing to sales enablement and product strategy.

Leads complex customer audits, due diligence, and RFI/RFP engagements; oversees compliance response quality, customer communications, governance, process improvement, tooling, and team development. Partners with Sales, Legal, Information Security, and executives to address high-risk inquiries, maintain response documentation, improve workflows, and ensure accurate, customer-ready outputs.

Drive enterprise software sales through prospecting, product demonstrations, technical value communication, negotiation, closing, and customer expansion. Serve as the primary customer contact, maintain CRM and forecasting data, collaborate with product and engineering teams, gather customer feedback, and support adoption. The role focuses on Replit’s AI-powered developer platform and requires London-area availability with travel up to 25%.

A 12-month graduate technology programme involving three rotations across software engineering, data, AI, banking, and compliance technology teams. Responsibilities include designing, building, testing, debugging, deploying, and improving software, platforms, applications, APIs, and data capabilities. Graduates will collaborate globally, gain exposure to analytics, automation, machine learning, and generative AI, and deliver practical technology solutions within a financial-services environment.

Conduct empirical AI safety research with mentor guidance, owning projects from hypotheses and controlled experiments through analysis and technical writing. Build and debug evaluation harnesses, agent environments, datasets, monitoring methods, and post-training experiments. Investigate model failures, alignment, deception, misuse, multi-agent risks, and evaluation reliability. Produce reproducible code, experiment logs, research analyses, and papers for potential submission to leading machine learning conferences.

Leads the EMEA and LATAM Advanced Services architecture delivery team, overseeing complex customer and partner projects across pre-sales and delivery. Responsibilities include recruiting and developing architects, collaborating with Sales, Product Management, Engineering, and Customer Experience, presenting enterprise solutions, managing escalations, ensuring customer satisfaction, and shaping the services portfolio. The role requires strategic services expertise, strong leadership, data-platform knowledge, executive communication, and the ability to travel extensively across the region.

Independently assess medical device software lifecycle processes and technical documentation under EU MDR, UK MDR, IEC standards, and related cybersecurity guidance. Review SaMD and AI-enabled devices, raise and resolve technical findings with manufacturers, interpret regulatory requirements, and deliver consistent assessments using established workflows with minimal oversight.

Support UK insurance pricing through price modeling, implementation, strategy, monitoring, and development of new products. The role balances pricing accuracy, profitability, and price-comparison competitiveness while collaborating with data scientists, product, and underwriting teams. It also involves developing pricing capabilities using actuarial methods, predictive modeling, machine learning, and AI, while continuing actuarial education and monitoring regulatory changes.

Leads AML transaction-monitoring optimization, rule testing, threshold tuning, scenario design, and false-positive reduction. Drives FIU automation and workflow improvements, evaluates AI and LLM tools, supports alert triage and investigations, and partners with Product, Engineering, Operations, and vendors on compliance technology integrations. Helps scale monitoring frameworks across products, jurisdictions, and transaction volumes while maintaining regulatory alignment.

Leads biostatistical activities for Phase II–III clinical trials, from protocol design through reporting and regulatory submission support. Responsibilities include statistical analysis planning, sample size calculations, SAP development, TLF review, database lock support, safety reporting, regulatory responses, and oversight of programming or CRO work. Collaborates with cross-functional clinical teams and uses SAS or R for analyses, modeling, simulation, exploratory work, and quality control. Coordinates statistical activities across studies and applies advanced statistical and machine learning methods.