Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Algorithms @ 7
Communication @ 7
Parallel Programming @ 4
Fraud @ 4
CUDA @ 4
GPU @ 4
AI @ 4
HPC @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
We are seeking a Senior AI Developer Technology Engineer to research and develop techniques to GPU-accelerate high-performance workloads at the intersection of AI and financial markets. The role partners with developer communities, industry and academic experts to analyze and optimize complex AI and HPC workloads for modern CPU and GPU architectures, publish findings, and influence next-generation hardware and software design.
Responsibilities
- Research and develop GPU-acceleration techniques for high-performance AI and financial workloads.
- Perform in-depth analysis and optimization of complex AI and HPC workloads on modern CPU and GPU architectures.
- Work directly with external technical experts (industry and academia) and internal teams (research, hardware, system software, libraries, tools).
- Publish and present optimization techniques in developer blogs, conferences, and workshops.
- Influence the design of next-generation hardware architectures, software, and programming models.
Requirements
- Advanced degree in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent experience.
- 5+ years of relevant work or research experience.
- Direct experience improving 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 (examples: CUDA, OpenACC, OpenMP, MPI, pthreads, TBB).
- In-depth expertise with CPU/GPU architecture fundamentals.
- Strong problem-solving, communication, and organizational skills.
Ways to Stand Out
- Master’s or PhD in a relevant field.
- Prior experience in capital markets with exposure to systematic/algorithmic strategies and quantitative trading.
- Experience parallelizing and optimizing ML algorithms (e.g., decision trees, time series models, Monte Carlo simulations).
- Deep knowledge of financial data models, pricing/risk simulation algorithms, portfolio optimization, or other finance-specific applications.
- Experience developing ML/DL techniques in finance (stock prediction, fraud detection, portfolio optimization).
Compensation & Benefits
- Base salary range (Level 3): 152,000 USD - 241,500 USD.
- Base salary range (Level 4): 184,000 USD - 287,500 USD.
- Eligible for equity and company benefits.
Additional Information
- Location: Santa Clara, CA, United States. #LI-Hybrid (hybrid work arrangement).
- Employment type: Full time.
- Applications accepted at least until March 13, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to diversity and inclusion.