Python Job: Python ML Engineer

Job added on


Plano, Texas - United States of America

Job type


Python Job Details

Job Description

A leader in the financial services industry is looking for a Python ML Engineer for their Plano, TX office. With a commitment to innovation, integrity, and excellence, this company has earned a reputation as one of the most trusted and member-centric financial institutions in the United States. They are dedicated to making a positive impact in the lives of their members and their families through tailored financial solutions and support.

In this role, you will be responsible for designing, developing, and deploying machine learning models that drive critical business decisions and enhance member experiences. You will collaborate with cross-functional teams to gather requirements, build robust data pipelines, and implement scalable solutions. Your expertise in Python and machine learning frameworks will be essential in developing innovative algorithms and applications. The ideal candidate will have a strong background in data science, excellent problem-solving skills, and a passion for leveraging technology to deliver measurable business outcomes.

Required Skills & Experience
  • 3+ years of experience with Python
  • Experience with Machine Learning tools - PyTorch/Tensorflow
  • Building out data pipelines
  • Experience with FAST API's
  • Experience building out API's from scratch
  • Experience with Snowflake
  • Experience with SQL
Desired Skills & Experience
  • Experience with EBT
  • Experience with AWS Cloud
Tech Breakdown
  • 50% MLE
  • 50% Data Engineering
Daily Responsibilities
  • 100% hands on MLE/Data
  • 100% collaborating with other team
  • 401(K)
  • Equity/stock options
  • Lots of room for growth
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Hybrid (4 days onsite / week)
  • Paid Time Off (PTO)
  • Professional development opportunities and continuous learning programs
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.