Hiring || Optimization Engineer (Performance & Cost)

Required Skills:

Summary The Optimisation Engineer (Performance & Cost) plays a pivotal role in advancing AI-driven operational excellence within a dynamic multi-disciplinary engineering team. Based in Bangalore this position is central to designing developing and deploying high-impact optimisation models that balance performance and cost efficiency across complex production and supply chain systems. The engineer will leverage rigorous mathematical modelling AI techniques and simulation frameworks to solve real-world operational challenges from production line balancing to supply chain optimisation. With end-to-end ownershipfrom concept to deploymentthis role drives the adoption of AI and optimisation technologies across technical and business functions ensuring scalable reliable and measurable outcomes. The ideal candidate will combine deep expertise in optimisation methodologies with hands-on development and infrastructure skills contributing to a culture of innovation efficiency and continuous improvement. Responsibilities Develop and train advanced AI and optimisation models focused on enhancing performance and reducing operational costs in real-world environments. Solve complex production and operational challenges using Linear Programming Mixed Integer Programming and Simulation Modelling techniques. Deploy and support AI-powered optimisation solutions ensuring seamless integration and adoption across internal and external stakeholders. Design and manage scalable compute infrastructure tailored for high-performance optimisation workloads and data pipelines. Lead initiatives to improve production efficiency through supply chain optimisation and production line balancing. Requirements Requirements: 7-12 years of experience in AI/ML engineering optimisation engineering DevOps or platform development with a proven track record in automotive or enterprise technology domains. Demonstrated expertise in Linear Programming Mixed Integer Programming Simulation Modelling and Digital Twin development. Hands-on experience in building deploying and maintaining scalable AI and optimisation systems in production environments. Proficient in Python (OR-Tools SciPy) cloud platforms (AWS Azure) and AI/ML frameworks. Experience with agile methodologies and collaboration tools such as JIRA and Confluence. Enablement Scope Manage provisioning and governance of AI/optimisation platforms and APIs including Python OR-Tools SciPy AWS Azure ML and Hugging Face. Establish and maintain high-performance compute clusters and scalable data pipelines for optimisation and AI workloads. Implement structured evaluation frameworks and Digital Twin systems using simulation modelling to monitor performance delivery success and AI adoption metrics. Strategic Impact Accelerate the transition from AI concept to production by delivering structured frameworks and scalable infrastructure. Bridge technical optimisation capabilities with business and operational needs to foster cross-functional innovation. Deliver measurable business value through cost reduction increased throughput and improved operational efficiency supported by clear KPI tracking and performance reporting. Preferred Traits High adaptability to emerging AI and optimisation technologies with a proactive mindset toward automation and process improvement. Strong analytical skills combined with a bias for execution delivery excellence and results-driven outcomes. Proven ability to thrive in fast-paced cross-functional environments with diverse stakeholder engagement. Passion for building scalable high-impact solutions that drive long-term operational efficiency and continuous improvement.

Required Education:

Graduate