HPC and Financial Workload Optimization Engineer

Job Description: The Role and Impact As a Software Enabling and Optimization Engineer, you will play a pivotal role in enhancing software performance and driving adoption of Intel products. You will collaborate with customers, software vendors, and the open-source community to develop, optimize, and differentiate software solutions across HPC and Financial domains. By delivering high-quality software enablement, testing, and optimization, you will contribute to advancing Intel's product capabilities and ensuring seamless user experiences. The successful candidate will combine strong software engineering and performance optimization skills with scientific and quantitative computing expertise, hands-on AI experience across HPC and financial workloads, customer engagement experience, and the ability to operate effectively across research, engineering, and business stakeholders. You will make extensive use of Intel's software tools and libraries to profile, tune, and accelerate customer applications on Intel platforms Business group The Data Center Group (DCG) is at the forefront of creating innovative solutions that address the needs of enterprise, cloud, and edge computing. This group focuses on enabling Intel technologies to shape the future of data-driven applications and scalable solutions. As part of DCG, you will contribute to Intel's leadership in high-performance computing and data-centric workloads, directly supporting Intel's broader goals of driving technological advancements. Key Responsibilities - Partner with customers and ecosystem software vendors to integrate, test, and optimize software solutions for Intel products. - Research, prototype, and develop software that leverages Intel's product capabilities to drive adoption across market segments. - Conduct performance tuning, debugging, and benchmarking to ensure differentiation and efficiency in software-enabled Intel technologies. - Deliver technical collateral, training materials, and differentiated benchmarks to support customer success and ecosystem enablement. - Influence product design, simulation, and projection strategies by identifying and driving key workloads into future product

. Qualifications: Minimum qualifications are required to be initially considered for this position. Master's degree in Computer Science, Computational Science, Engineering, Physics, Mathematics, Financial Engineering, or a related technical discipline, or equivalent professional experience. Experience in software development, scientific or quantitative computing, HPC or other workload optimization, application engineering, or a closely related field. Strong programming skills in C and/or C++, together with experience using Python or another modern scripting language. Experience working in Linux or UNIX-based HPC or high-performance financial computing environments. Experience with parallel programming technologies such as MPI and OpenMP. Experience with software performance analysis, profiling, benchmarking, debugging, and optimization. Ability to understand complex customer workloads and collaborate with internal engineering teams to drive issue resolution. Strong written and verbal communication skills in English, including presenting technical material to expert audiences. Ability to manage multiple technical workstreams and operate independently in a customer-facing environment. Preferred Qualifications Experience supporting HPC centers, research institutions, large-scale scientific computing deployments, or financial-services trading, risk, and analytics platforms. Experience with accelerator programming technologies such as SYCL, OpenMP target offload, CUDA, or OpenCL. Experience optimizing applications in domains such as physics, engineering simulation, computational chemistry, climate and weather, life sciences, AI for science, or financial workloads such as risk management, pricing, quantitative research, and real-time trading. Experience with compilers, numerical and communication libraries, AI frameworks, and HPC/FSI performance analysis tools. Familiarity with cluster environment, workload schedulers, networking, storage, low-latency interconnects, and software environment management. Experience building sustained technical relationships with customers, academic researchers, financial-services technology teams, and ecosystem partners. Demonstrated experience applying AI-enhanced methods in HPC or FSI environments, such as integrating AI into scientific or financial workflows, accelerating AI workloads on HPC/FSI systems