Senior AI Developer Technology Engineer, Financial Sector

NVIDIA is seeking a Senior AI Developer Technology Engineer in the Financial Sector to help shape the future of financial AI and data analytics. The role involves researching and developing techniques to GPU-accelerate high-performance workloads while collaborating with technical experts to optimize complex AI and HPC workloads.

Responsibilities:

• Research and develop techniques to GPU-accelerate high-performance workloads at the intersection of AI and financial markets
• Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC workloads to ensure the best possible performance on modern CPU and GPU architectures
• Publish and present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the Developer community
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA

Requirements:

• An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience)
• You have 5+ years of relevant work or research experience
• Direct experience improving the performance of large computational applications used by financial institutions
• Excellent understanding of linear algebra
• Programming fluency in C/C++ with a deep understanding of algorithms and software design
• Hands-on experience with low-level parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, TBB, etc
• In-depth expertise with CPU/GPU architecture fundamentals
• Good communication and organization skills, with a logical approach to problem solving, and prioritization skills
• A Master's or PhD in a relevant field is highly valued
• Prior work experience in capital markets with exposure to systematic/algorithmic strategies and quantitative trading
• Experience with parallelizing and optimizing machine learning algorithms like decision trees, time series, and Monte Carlo simulations
• Deep knowledge of financial data models, pricing/risk simulation algorithms, portfolio optimization, or other financial specific applications/ services
• Have developed ML/DL techniques in the finance space, such as stock market prediction, fraud detection, portfolio optimization/selection