What are the responsibilities and job description for the Remote - Machine Learning Engineer position at State Farm?

Remote - Machine Learning Engineer

US-IL-Bloomington

Job ID : 2025-40596

Type : Regular Full Time

of Openings : 4

Category : Research and Data Analytics

Bloomington, IL

Overview

Being good neighbors - helping people, investing in our communities, and making the world a better place - is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good!

SPONSORSHIP : Applicants for this position are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity.

REMOTE : Qualified candidates residing more than 50 miles from a hub location listed below may be considered for 100% remote work arrangements based on where a candidate currently resides or is currently located.

HYBRID : Qualified candidates residing within 50 miles radius of a hub location listed below will be classified as a Hybrid employee. In a hybrid work arrangement, you will be able to work remotely most of the time with in-office expectations of 1 per quarter. This could consist of a multi-day event per quarter depending on your leader and business need. Any business travel associated with your in office expectation would be at your own expense. Your manager will share additional details with you regarding your departments approach and what it means for you.

HUB LOCATIONS : Dunwoody, GA; Richardson, TX; Tempe, AZ; or Bloomington, IL

Responsibilities

Are you a passionate Machine Learning Engineer looking for an opportunity to make a significant impact? Join our team at State Farm and play an integral role in building and supporting advanced analytic solutions that are used across the enterprise. As a Machine Learning Engineer, you will be responsible for deploying data science solutions, optimizing analytic workflows, and assisting with analytic research requests. Your work will directly contribute to the increased use of advanced analytics for decision making throughout the company.

At State Farm, we believe in fostering professional growth and development. As part of our Machine Learning Engineering team, you will have the opportunity to expand your skill set across multiple development areas. Interacting with key business partners will enhance your communication skills, as you learn to effectively explain technical concepts in a non-technical way. The diverse range of projects you will work on will refine your knowledge in advanced analytic topics, software development practices, and tool development for department use.

We understand the importance of keeping your skills sharp in a rapidly evolving field. That's why this role offers practical research opportunities and continued professional development. You will have the chance to learn and leverage cutting-edge tools and explore various programming languages.

Join us at State Farm and be part of a team that values innovation, collaboration, and making a difference. Your expertise and passion for machine learning will be instrumental in driving our success.

Qualifications

Bachelor's degree in Computer Science, Software Engineering, or Data Science.

2 years of professional, post-internship work experience in a computer science or technology-related field (e.g., DevOps engineering, software engineering, development).

Proficiency in Python 3 and relevant libraries (e.g., Pandas, Numpy, Scikit-learn, FastAPI, Flask, Tensorflow, PyTorch).

Familiarity with model validation metrics, including data drift metrics (e.g., population stability index, Kolmogorov-Smirnov test) and model drift metrics (e.g., F1 score, ROC AUC score, RMSE).

Understanding of software engineering concepts, including classes, functions, version control, CI / CD, and unit tests.

Experience deploying models for batch, synchronous, and / or asynchronous consumption.

Technical expertise in Linux, AWS, and Kubernetes.

Preferred Qualifications :

Familiarity with advanced analytic algorithms, including binary classification algorithms, regression algorithms, Neural Network frameworks, and Natural Language Processing.

Knowledge of Containerization using Docker.

Experience with deployment through HashiCorp Terraform and Scalr.

Understanding of credential management using HashiCorp Vault.

Experience in gathering and creating analytic business requirements, researching data sources (internal and external), and developing and maintaining data assets.

The Selection Process :

After submitting your application, our recruitment team will carefully review your qualifications. If your profile aligns with our requirements, you may progress to the next stage of the selection process.

The initial assessment will involve a take-home work assignment. This assignment will allow you to showcase your skills and abilities in a practical setting. Once you have completed and submitted the take-home work assignment, our team of experienced Machine Learning Engineers will evaluate your results.

If selected to move forward, you will have the opportunity to participate in a Live Video interview with members of our hiring team. This interview will provide a chance for us to further assess your technical expertise and suitability for the role.

Following the successful completion of the Hiring Team round, competitive candidates may be invited to the final stage of the process : the virtual onsite interview. This round will involve interviews with members of our hiring panel, allowing us to gain deeper insights into your skills, and experiences.

We appreciate your interest in joining our team as a Machine Learning Engineer.

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