Solution Architect, Financial Services

NVIDIA NVIDIA · Semiconductors · Cambridge, MA, United Kingdom +5 · Remote

Solutions Architect for Financial Services at NVIDIA, focusing on guiding customers in leveraging NVIDIA's AI technologies, particularly in areas like model distillation, domain adaptation, reinforcement learning, and post-training algorithms. The role involves technical advocacy, collaborative innovation, and knowledge sharing within the financial services sector, requiring expertise in AI frameworks, Python, distributed computing, and the AI model lifecycle.

What you'd actually do

  1. Guide customers in implementing next-generation model distillation, domain adaptation, reinforcement learning (RL), and post-training algorithms by helping them adopt NVIDIA AI SDKs and APIs.
  2. Work with financial institutions and their technology ecosystem to leverage NVIDIA's advanced technologies.
  3. Improve NVIDIA products and build creative solutions to overcome scaling challenges at the intersection of computer architecture, libraries, and AI applications.
  4. Work closely with product management, engineering, applied research, and sales teams to develop and deliver comprehensive solutions.
  5. Be part of the team that helps bring NVIDIA technology to life in the Enterprise, acting as the face and trusted expert advisor that our customers and partners rely on.

Skills

Required

  • BS, MS, or PhD degree in Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related technical field
  • Financial Services Background
  • 5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers
  • Strong Python programming, software design, and debugging skills
  • Deep understanding of distributed computing and parallelism methodologies (model and data parallelism)
  • Good understanding or hands-on experience with CUDA
  • Experience with AI model lifecycle components, including pre-training, supervised fine-tuning, and model evaluation
  • Adaptability
  • Clear written and oral communication skills

Nice to have

  • Deep expertise in writing and optimizing code for training and/or inference specifically for NVIDIA GPUs
  • Experience with or contributions to NVIDIA deep learning frameworks, particularly NeMo, Megatron Core, or NeMo-RL
  • Demonstrated understanding of how GPU acceleration can be applied specifically to financial workloads (e.g., algorithmic trading, risk modeling)
  • Hands-on experience in large-scale foundation model training, accuracy, and performance profiling
  • Experience with distributed computing tools like SLURM and Kubernetes for training large models on GPUs

What the JD emphasized

  • Proven experience working within Financial Services firms
  • 5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers
  • Experience with AI model lifecycle components, including pre-training, supervised fine-tuning, and model evaluation

Other signals

  • customer-facing technical advisor
  • enabling customer productivity
  • driving adoption of NVIDIA AI technology
  • guidance on model distillation, domain adaptation, RL, and post-training algorithms
  • experience with AI frameworks and libraries
  • experience with AI model lifecycle components, including pre-training, supervised fine-tuning, and model evaluation