Business Optimization & AI Model Specialist

What success looks like in this role: AI-Driven & Hybrid Optimization Techniques • Design and develop hybrid AI–optimisation techniques that fuse machine learning, metaheuristics, and exact solvers to deliver efficient, scalable AI solutions. • Apply optimisation methods to improve the efficiency of AI itself, including hyperparameter optimisation, neural architecture search, and model compression techniques such as pruning and quantisation. • Leverage AI/ML models (including large language models and neural combinatorial optimisation approaches) to accelerate model formulation, warm-start solvers, and automate solution-space exploration. • Build data-driven pipelines that integrate predictive ML models with prescriptive optimisation engines to enable end-to-end intelligent decision-making. • Evaluate trade-offs between accuracy, computational cost, and energy efficiency to ensure AI-enhanced optimisation solutions are sustainable and production-ready. Integration of Hybrid Advanced Metaheuristic, AI and HPC • Collaborate closely with our Quantum, AI, and HPC R&D teams to identify high-value combinatorial problems where quantum computing and AI acceleration can offer a computational advantage. • Develop proof-of-concept (PoC) studies that compare classical optimisation techniques with quantum/hybrid and AI-augmented approaches. • Work with software developer solution engineers to integrate HPC-powered and GPU-accelerated AI solvers for large-scale combinatorial optimisation problems. • Support the deployment and monitoring of AI-enhanced optimisation models in production environments, applying MLOps best practices for reproducibility, versioning, and performance tracking. Industry Applications & NextGen Advisory • Develop AI-powered decision support systems and prescriptive analytics solutions for clients in finance, logistics, cybersecurity, and smart infrastructure. • Advise clients on adopting hybrid AI–optimisation strategies, including responsible and efficient use of AI in enterprise decision-making. • Provide leadership and contribute to white papers, patents, and publications on innovative quantum, AI, and hybrid optimisation methodologies. You will be successful in this role if you have: Applies the principles of secure software engineering to the design, development, maintenance, testing and evaluation of software and cloud infrastructure. Works cross-functionally to understand business requirements, architecture and technology direction, evaluate alternative approaches and ensure software and systems are designed accordingly. Incorporates state-of-the-art concepts and practices — including artificial intelligence and machine learning — to facilitate system functionality, scalability, resilience and security as well as ease-of-use. Applies agile principles to software development with a focus on delivery of business value, collaboration, continuous improvement and sustainability. Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law. Local employment practices and rights may vary by jurisdiction and are subject to applicable local laws. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers. If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at GlobalRecruiting@unisys.com . US job seekers can find more information about Unisys’ EEO commitment here .