We’re currently seeking an AI Developer in the Financial Sector! 

Would you enjoy researching parallel algorithms to accelerate end to end financial AI and data analytics workloads on advanced computer architectures? Is it rewarding to investigate, find, and eliminate system bottlenecks to achieve the best possible performance of computer hardware? 

Could you be thrilled about an opportunity to partner with the Developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader? 

If so, we invite you to consider this role.

What You Will Be Doing 

• In this position, you will research and develop techniques to GPU-accelerate high-performance workloads in the finance domain - primarily focusing on Deep Learning, Machine Learning and Data Analytics applications. 

• 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. 

What we must see:

• An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience). 

• You have 3 years of relevant work or research experience. 

• Direct experience improving the performance of large computational applications used by financial institutions. 

• 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. Ways To Stand Out From The Crowd 

• A Master’s or PhD in a relevant field is highly valued. 

• Technical leadership skills, e.g., managing small engineering teams very helpful. 

• 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. 

• Excellent understanding of linear algebra. 

• Have developed ML/DL techniques in the finance space, such as stock market prediction, fraud detection, portfolio optimization/selection. 

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This role plays a crucial role in the success of our brand and our customers. Your work with external technologists to investigate performance of their applications, design parallel algorithms and implement optimizations in a GPU accelerated computing environment.