Key skills
GPU-accelerated computingParallel programmingCUDAOpenACCOpenMPMPIpthreadsTBBC++CAlgorithmsSoftware designCPU architectureGPU architectureLinear algebraFinancial computational applicationsMachine learning algorithmsMonte Carlo simulationsDecision treesTime series analysisFinancial data modelsPricing algorithmsRisk simulation algorithmsPortfolio optimizationAIMachine LearningMLCommunicationProblem SolvingCollaboration
About this role
NVIDIA is a leader in AI and computing technology, and they are seeking a Senior AI Developer Technology Engineer for the Financial Sector. This role involves researching and optimizing high-performance workloads at the intersection of AI and financial markets, collaborating with technical experts, and publishing findings to the developer community.
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