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WEX Inc.

Staff AI Engineer

Reposted 16 Days Ago
In-Office or Remote
12 Locations
Senior level
In-Office or Remote
12 Locations
Senior level
The Staff AI Engineer will design, implement, and maintain machine learning algorithms and systems, integrating AI components into applications and collaborating with cross-functional teams using cloud technologies and DevOps principles.
The summary above was generated by AI
This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.About the Team/Role

We are the AI Engineering team at WEX.  We enable our product development teams to move quickly and deploy AI functionality into their applications in a scalable manner.  We are cloud-first and aim to automate everything, including  infrastructure, testing, and deployment.  If you’re interested in ChatGPT, Large Language Models, MLOps, DevOps, and thirst for working with new tools and technologies, then this is the place to be!

How you’ll make an impact
  • A highly motivated engineer who loves working on small, highly performing teams

  • Collaborative, a solid communicator, and work well with your team and stakeholders.

  • A professional who can advocate strongly for positions and still be 100% behind team decisions even if they don’t go your way.

  • Are comfortable balancing the need to move fast with the realities of working in highly regulated spaces like payments and healthcare.

  • Design, implement, train and maintain machine learning algorithms and ML system pipelines.

  • Work closely with our AI platform team and line of business engineering teams to integrate AI components and models into WEX systems.

  • Collaborate with the team to manage version control using GitHub and implement robust CI/CD pipelines for continuous integration and delivery.

  • Design and implement RESTful APIs to facilitate communication between various components and ensure smooth operation of our applications.

  • Collaborate effectively with cross-functional teams, participate in code reviews, and communicate solutions to both technical and non-technical stakeholders.

Experience you’ll bring

  • Minimum 10 years of application development experience.

  • Strong ability to use key Python libraries such as Pandas, Numpy and deep learning libraries like PyTorch or Tensorflow.

  • Bachelor's Degree in Computer Science, Engineering, or related field.

  • Familiarity with cloud technologies, such as AWS, Azure, or GCP and how to provision those services through IAC frameworks such as Terraform.

  • Experience applying DevOps principles to software development processes.

  • Proficiency in version control systems, particularly GitHub.

  • Excellent problem-solving skills and a proactive approach to addressing challenges.

  • Experience in the financial industry is a plus.

  • Experience in building Agentic AI Applications

Nice to have

Experience building, training and deploying machine learning models.

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $185,000.00 - $217,400.00

Top Skills

AWS
Azure
Ci/Cd
GCP
Git
Numpy
Pandas
Python
PyTorch
Restful Apis
TensorFlow
Terraform

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