Wells Fargoposted 4 days ago
$159,000 - $305,000/Yr
Full-time
Hybrid • Charlotte, NC
Credit Intermediation and Related Activities

About the position

We are seeking a High-Performance Computing (HPC) Engineer with experience in Machine Learning to optimize and scale AI/ML workloads. The ideal candidate will have experience with distributed training, model parallelization, GPU acceleration, and performance optimization across diverse hardware platforms. Experience or strong interest in Large Quantitative Models of High-Frequency Time Series is a strong advantage.

Responsibilities

  • Design, develop, and optimize HPC solutions for large-scale ML workloads.
  • Optimize data pipelines for high-throughput model training (Dask, Ray, NVIDIA RAPIDS).
  • Profile, optimize, and accelerate deep learning models on GPUs, TPUs, and multi-node clusters.
  • Work on low-level performance tuning - vectorization, memory optimization.
  • Develop and benchmark custom kernels for AI models using CUDA, ROCm, OpenACC, OpenMM.
  • Implement distributed training strategies using MPI, DeepSpeed, PyTorch/XLA.
  • Collaborate with ML researchers and engineers to deploy scalable ML models.
  • Research and implement new HPC techniques.
  • Evaluate and adopt new technologies like Distributed Ledger or Blockchain.
  • Create new solutions to be deployed along existing enterprise software.
  • Work as part of team that follows the agile methodology.
  • Lead and mentor junior developers who are learning advanced technologies.
  • Lead or participate in complex initiatives on selected domains.
  • Assure quality, security and compliance for supported systems and applications.
  • Serve as a technical resource in finding software solutions.
  • Review and evaluate user needs and determine requirements.
  • Provide technical support, advice, and consultation with the issues relating to supported applications.
  • Create test data and conduct interfaces and unit tests.
  • Design, code, test, debug and document programs using Agile development practices.
  • Understand and participate to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives.
  • Conduct research and resolve problems in relation to processes and recommend solutions and process improvements.
  • Assist other individuals in advanced software development.
  • Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals.

Requirements

  • 5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
  • 1 year experience in HPC & Parallel Computing: distributed computing frameworks, multi-threading, and vectorization techniques. Hands-on experience with GPU computing.
  • 1 year experience optimizing ML workloads on NVIDIA, AMD, or custom AI Accelerators.
  • 1 year experience in Machine Learning Optimization: Frameworks as PyTorch, TensorFlow, JAX. Model parallelization (pipeline and tensor parallelism).
  • 1 year Data Processing and I/O optimization experience: Large datasets processing with Parallel I/O. Optimization of memory and data storage.
  • 1 year experience with Cluster HPC, HPC schedulers and familiarity with cloud-based HPC (AWS Parallel Cluster, Azure ML, Google Cloud TPUs).

Nice-to-haves

  • Advanced degree (M.S./Ph.D.) in computer science or physics.
  • Knowledge and experience developing models in financial instruments pricing and portfolio risk management.
  • Hands-on experience in deploying ML workloads on large-scale HPC clusters.

Benefits

  • Health benefits
  • 401(k) Plan
  • Paid time off
  • Disability benefits
  • Life insurance, critical illness insurance, and accident insurance
  • Parental leave
  • Critical caregiving leave
  • Discounts and savings
  • Commuter benefits
  • Tuition reimbursement
  • Scholarships for dependent children
  • Adoption reimbursement
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