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.
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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.
- 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.
- 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.
- 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
- 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
- CA and NY - $115,900.00 - $206,100.00 Annual
- Other locations- $96,600.00 - 171,800.00 Annual
- Information about Wells Fargo's US employee benefits
- Information about Wells Fargo's International employee benefits
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
31 Jul 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.
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To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
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Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
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