Technical Product Manager – HPC​/Quant

Seeking a Technical Product Manager (TPM) with deep experience in High Performance Computing (HPC) — ideally with firsthand experience managing or running quantitative finance, risk modeling, or large-scale simulation workloads (e.g., Monte Carlo simulations, backtesting frameworks, or computational econometrics), or managing products that accomplish those goals. This role sits at the intersection of engineering, product, and research, responsible for translating demanding compute requirements into scalable infrastructure and performant products that enable researchers and data scientists to move faster.

• Product Strategy & Vision: Define and deliver a roadmap for our HPC platform and related compute products, aligning with business goals and research priorities.
• Workload Enablement: Partner with quantitative researchers and data scientists to understand complex workload characteristics — including latency, parallelization, memory scaling, and data locality — and ensure infrastructure products meet or exceed their performance needs.
• Technical Product Design: Collaborate closely with HPC engineering, storage, and networking teams to design, benchmark, and iterate on systems that optimize for throughput, cost, and reliability at scale.
• Performance Optimization: Analyze and interpret workload telemetry and performance metrics to guide continuous improvement across compute, job scheduling, and data handling layers.
• Cross-Functional Leadership: Drive alignment between research, infrastructure, and operations teams to ensure successful delivery of new features, clusters, or capabilities.
• Market & Technology Intelligence: Stay informed about trends in HPC, GPU acceleration, distributed systems, and workload orchestration (e.g., Slurm, Kubernetes, or cloud-HPC hybrids) to inform product strategy.
• Risk & Delivery Management: Identify technical and operational risks early, and develop pragmatic mitigation plans to ensure consistent, high-quality product delivery.

• Experience: Proven track record as a Product Manager or Technical Product Owner in HPC, Cloud Infrastructure, or large-scale compute environments. Experience working directly with quantitative research, scientific simulation, or AI/ML training workloads is strongly preferred.
• Technical Depth: Understanding of HPC architectures, parallel computing models (MPI, CUDA, OpenMP), workload scheduling, and performance profiling. Experience with on-prem or hybrid HPC environments, and with major cloud providers’ HPC offerings (AWS Parallel Cluster, Azure Cycle Cloud, or Google Batch).
• Analytical Mindset: Strong data-driven approach to decision making, with familiarity in interpreting performance metrics, utilization data, and cost models.
• Communication & Leadership: Excellent communicator who can bridge technical and non-technical teams. Demonstrated ability to lead cross-functional initiatives.
• Customer Orientation: Empathy for end users — particularly researchers, data scientists, and engineers — with the ability to translate their needs into technical priorities.
• Education: Bachelor’s degree in Computer Science, Engineering, Physics, or a related technical discipline; equivalent experience also valued.