Optimization Engineer (3-8 Years of experience in AI and optimisation models

Job Title: Optimisation Engineer (Performance & Cost) Role Overview Were building a multi-disciplinary engineering team that blends platform, application, and development expertise to deliver AI-driven internal projects and enable external collaborations. This role focuses on solving complex production and trade-off problems using high-rigour mathematical modelling, AI techniques, and simulation frameworks. The position requires end-to-end executionfrom requirement analysis to deploymentwhile driving adoption of AI technologies across business and technical functions. The role demands strong optimisation expertise, hands-on development skills, and a commitment to scalable delivery, cost efficiency, and continuous improvement. Key Responsibilities Develop and train advanced AI and optimisation models with a focus on performance and cost efficiency in real-world scenarios. Solve complex production and operational problems using Linear Programming, Mixed Integer Programming, and Simulation Modelling techniques. Deploy and support AI-driven optimisation solutions , ensuring smooth adoption across internal and external stakeholders. Architect and manage scalable compute infrastructure for high-performance optimisation workloads and data pipelines. Drive production efficiency improvements through supply chain optimisation and production line balancing. Enablement Scope Licenses & Tools: Manage provisioning of AI/optimisation platforms and APIs (e.g., Python OR-Tools, SciPy, AWS, Azure ML, Hugging Face). Infrastructure: Establish high-performance compute clusters and scalable data pipelines for optimisation and AI workloads. Assessment: Implement structured evaluation frameworks and Digital Twins using simulation modelling to track system performance, delivery success, and AI adoption. Strategic Impact Accelerate AI adoption by enabling faster transition from concept to production through structured frameworks and scalable infrastructure. Enable cross-functional innovation by bridging AI optimisation capabilities with business and operational needs. Drive measurable business outcomes through cost reduction, improved efficiency, and increased production throughput with clear KPI tracking. Qualifications 5+ years of experience in AI/ML engineering, optimisation engineering, DevOps, or platform development, preferably in automotive or enterprise technology. Strong expertise in Linear Programming, Mixed Integer Programming, Simulation Modelling, and Digital Twin development. Proven experience in model development, deployment, and infrastructure setup for scalable AI systems. Strong knowledge of Python (OR-Tools, SciPy), cloud platforms (AWS, Azure), and AI/ML frameworks. Familiarity with agile methodologies and tools such as JIRA and Confluence. Preferred Traits High adaptability to emerging AI and optimisation technologies with a proactive automation mindset. Strong analytical thinking with a bias for execution and delivery excellence. Ability to work in fast-paced, cross-functional environments with multiple stakeholders. Passion for building scalable, high-impact solutions that drive operational efficiency and continuous improvement. Please share your profiles to View email address on click.appcast.io with below details: Total yrs. of exp: CCTC: ECTC: NP: Disclaimer - At Stellantis, we assess candidates based on qualifications, merit and business needs. We welcome applications from people of all gender identities, age, ethnicity, nationality, religion, sexual orientation and disability. Diverse teams will allow us to better meet the evolving needs of our customers and care for our future. By submitting your application, you are accepting our privacy notice: Job Title: Optimisation Engineer (Performance & Cost) Role Overview Were building a multi-disciplinary engineering team that blends platform, application, and development expertise to deliver AI-driven internal projects and enable external collaborations. This role focuses on solving complex production and trade-off problems using high-rigour mathematical modelling, AI techniques, and simulation frameworks. The position requires end-to-end executionfrom requirement analysis to deploymentwhile driving adoption of AI technologies across business and technical functions. The role demands strong optimisation expertise, hands-on development skills, and a commitment to scalable delivery, cost efficiency, and continuous improvement. Key Responsibilities Develop and train advanced AI and optimisation models with a focus on performance and cost efficiency in real-world scenarios. Solve complex production and operational problems using Linear Programming, Mixed Integer Programming, and Simulation Modelling techniques. Deploy and support AI-driven optimisation solu