APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

WELLS FARGO RECRUITMENT AND HIRING REQUIREMENTS:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process

Required Qualifications:

• 4+ 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 paralelization (pipe-line and tensor paralelism)
• 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

Desired Qualifications:

• 1+ years of experience in HPC, ML optimization or/and infrastructure.
• Hands-on experience in deploying ML workloads on large-scale HPC clusters
• M.S./Ph.D. in Computer science or related field is a plus, Academic work (thresis, research articles, projects, etc.) in the areas of interest mentioned above count as work experience

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.
Learn more about the career areas and lines of business at wellsfargojobs.com

In this role, you will:

• 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.
• 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.

Required Qualifications:

• 4+ 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 paralelization (pipe-line and tensor paralelism)
• 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.

Desired Qualifications:

• 1+ years of experience in HPC, ML optimization or/and infrastructure.
• Hands-on experience in deploying ML workloads on large-scale HPC clusters
• M.S./Ph.D. in Computer science or related field is a plus, Academic work (thresis, research articles, projects, etc.) in the areas of interest mentioned above count as work experience.

Job Expectations:

• Wells Fargo will only consider candidates who are presently authorized to work for any employer in the United States and who do not require work visa sponsorship from Wells Fargo now or in the future in order to retain their authorization to work in the United States.
• This position offers a hybrid work schedule
• Relocation assistance is not available for this position

Locations:

• 150 E. 42nd Street, New York, New York
• 333 Market St., San Francisco, California
• 300 S. Brevard St., Charlotte, NC
• 3075 Loyalty Circle, Columbus ,OH
• 1301 Solana Blvd., Westlake, TX
• 800 S Jordan Creek Pkwy, Des Moines, IA
• 2600 S Price Road, Chandler, AZ

Pay Range:

• CA and NY - $115,900.00 - $206,100.00 Annual
• Other locations- $96,600.00 - 171,800.00 Annual

Benefits:

• Information about Wells Fargo’s US employee benefits
• Information about Wells Fargo’s International employee benefits