About this role:

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:

Posting End Date:

18 Apr 2025

*Job posting may come down early due to volume of applicants

Pay Range

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.

$96,600.00 - $206,100.00

Benefits

Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.

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

Posting End Date:

1 May 2025

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Applicants with Disabilities

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

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

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.