Machine Learning Engineer - (REMOTE)

Key Skills

AWS, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, DevOps, Docker, FastAPI, Flask, Kubernetes-K8s, Machine learning techniques, Natural Language Processing (NLP), NumPy, Pandas, Python Programming, PyTorch, Scikit-learn, TensorFlow, Terraform

Job Description

Responsibilities

As a Machine Learning Engineer, you will play an integral role within State Farm for helping build and support advanced analytic solutions that are used across the enterprise. Machine Learning Engineers are responsible for helping deploy data science solutions, build solutions that optimize analytic workflows, and assisting with analytic research requests. With this role, your work will help increase use of advanced analytics for decision making throughout the company.

Being part of the Machine Learning Engineering team at State Farm will help facilitate your professional growth across multiple development areas. First, you will strengthen your communication skills through interactions with key business partners that require you to articulate technical concepts in a non-technical way. Additionally, the variety of projects that you work on will allow you to refine your knowledge for advanced analytic topics, software development practices, and tool development for use by the department. Finally, to help keep your skills sharp, this role includes an opportunity for practical research and continued professional development with opportunities to learn and leverage cutting edge tools and many different programming languages.

Qualifications

Preferred Skills & Professional Experience:

• Completed Bachelors, other advanced degrees, and 2+ years' experience in a computer science or technology related field such as DevOps engineering, software engineering, or developer.
• Proficiency with Python 3+, including libraries such as Pandas, Numpy, Scikit-learn, FastAPI, Flask, Tensorflow, PyTorch.
• Experience with gathering and creating analytic business requirements, researching potential data sources (both internal and external sources), designing, developing, and maintaining data assets.
• Familiarity with algorithms associated advanced analytic topics, including binary classification algorithms, regression algorithms, Neural Network frameworks, and Natural Language Processing.
• Familiarity with various 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).
• Demonstrated understanding of software engineering topics, including classes, functions, version control, CI/CD, and unit tests.
• Experience deploying models for batch, synchronous, and/or asynchronous consumption.
• Technical expertise with multiple compute environments, including Linux, AWS, and Kubernetes.
• Familiarity with Containerization through Docker.
• Familiarity with deployment through HashiCorp Terraform.
• Familiarity with credential management through HashiCorp Vault.

For Los Angeles candidates: Pursuant to the Los Angeles Fair Chance Initiative for Hiring, we will consider for employment qualified applicants with criminal histories. 

For San Francisco candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 

For Colorado candidates: Potential Salary Range: $94,006.00 - $174,900.00 

For CA, NYC and CT candidates: Potential Salary Range: $106,825 - $198,750

Competitive Benefits, including:

• 401k Plan
• Health Insurance
• Dental/Vision plans
• Life Insurance
• Paid Time Off
• Annual Merit Increases
• Tuition Reimbursement
• Health Initiatives