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Tier-1 brand and metro location increase competition, but specialized HPC requirements limit applicant pool.
Highly domain-specific HPC and financial risk experience limits cross-industry transferability.
Explicit 8+ years, cloud provider expertise, Kubernetes, C++/Python, and finance/HPC experience make filters strict.
Architect, build, and manage a massive-scale distributed compute grid on public cloud platforms (AWS, GCP) to run financial pricing models at scale.
Design and implement orchestration layer distributing millions of pricing tasks across hundreds of thousands of CPU/GPU cores with high availability and efficiency.
Collaborate with quantitative teams to integrate and optimize a library of pricing models, ensuring fast, reliable risk valuation meeting regulatory requirements.
8+ years professional experience designing, building, and running applications on massive-scale compute grids.
Expert hands-on experience with AWS or GCP including batch processing, containerization, and serverless technologies.
Strong programming skills in C++ and Python; expertise with Docker and Kubernetes for container orchestration.
Bachelor’s degree in Computer Science, Engineering, or related technical field.
Proven track record in financial industry HPC use cases such as Monte Carlo simulations, VaR calculations, or XVA grids.
Strong background in distributed systems, infrastructure-as-code, performance tuning, and cost optimization of cloud resources.
Experience operating in high-pressure, large-scale environments collaborating closely with quantitative research, trading, and risk management teams.