Lead Machine Learning Engineer at Wells Fargo
Chandler, Arizona, USA -
Full Time


Start Date

Immediate

Expiry Date

19 Nov, 25

Salary

224000.0

Posted On

20 Aug, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Automation, Training, Kubernetes, Analytical Skills, Scripting, Docker

Industry

Information Technology/IT

Description

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.
$119,000.00 - $224,000.00

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:

  • 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • 5+ years of experience in platform engineering, with a focus on AI/ML technologies.
  • 3+ years experience with AI/ML frameworks and tools (e.g., Spark, PyTorch, Kubernetes, Docker)

Desired Qualifications:

  • Proficiency in cloud platforms, particularly GCP.
  • Knowledge of on-premises Kubernetes platforms (preferably RH OpenShift)
  • Expertise in scripting and automation (e.g., Python, Bash, Terraform).
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and as part of a team.
  • GCP Professional Cloud Architect or similar certifications
Responsibilities

Wells Fargo is seeking a highly skilled and experienced Lead Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, implementing, and maintaining AI platforms both on-premises and in Google Cloud Platform (GCP). This role requires an understanding of AI/ML technologies, cloud infrastructure, and on-premises systems. This Senior Engineer will work closely with cross-functional teams to ensure the seamless integration and operation of AI solutions.

In this role, you will:

  • Lead complex technology initiatives including those that are companywide with broad impact
  • Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
  • Design, code, test, debug, and document for projects and programs
  • Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors
  • Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
  • Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
  • Lead projects, teams, or serve as a peer mentor
  • Architect and deploy AI platforms on-premises and in GCP, ensuring scalability, reliability, and performance.
  • Provision and design optimized GCP cloud infrastructure using tools such as Terraform to support AI workloads, including compute, storage, and networking resources.
  • Work with data scientists, MLOPs engineers, and other stakeholders to understand requirements and deliver robust and scalable AI solutions.
  • Ensure that AI platforms adhere to security best practices and compliance requirements.
  • Monitor and optimize the performance of AI platforms, identifying and resolving bottlenecks.
  • Create and maintain comprehensive documentation for AI platform architecture and runbook content on net new technology for Platform Support team

Required Qualifications:

  • 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • 5+ years of experience in platform engineering, with a focus on AI/ML technologies.
  • 3+ years experience with AI/ML frameworks and tools (e.g., Spark, PyTorch, Kubernetes, Docker).

Desired Qualifications:

  • Proficiency in cloud platforms, particularly GCP.
  • Knowledge of on-premises Kubernetes platforms (preferably RH OpenShift)
  • Expertise in scripting and automation (e.g., Python, Bash, Terraform).
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and as part of a team.
  • GCP Professional Cloud Architect or similar certifications.

Job Expectations:

  • Position will require onsite presence at one of the required locations listed below in a hybrid work schedule
  • This position in not eligible for Visa sponsorship
  • Relocation assistance is not available for this position
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