Progressive InsuranceRemote
Senior/Lead Machine Learning Data Engineer
United States of America
Full Time
4 hours ago
$118,000 - $165,000 USD
No H1B
Key skills
PythonAWS S3AWS EC2AWS LambdaUnix Shell scriptingBashSnowflakeTectonTerraformDockerPrefectApache SparkSQLMachine learning model deploymentMachine learning algorithmsReal-time data stream processingCI/CD automationGitGitHub ActionsAzure DevOpsShellMachine LearningSparkAWSAzureEC2S3GitHubCI/CD
About this role
Progressive Insurance is dedicated to helping employees move forward and live fully in their careers. As a senior or lead machine learning data engineer, you’ll be responsible for developing machine learning platform solutions and building necessary data pipelines to support Data Science models.
Responsibilities:
- Work on a Claims IT team focused on developing machine learning platform solutions for machine learning operations and deployment
- Use data-focused software engineering and languages like Python to solve problems with techniques you may need to research, learn, and implement
- Develop and deploy the machine learning platform
- Build and deploy these solutions leveraging cloud services and resources from cloud providers
- Build out the necessary data pipelines to support Data Science models
- Enable efficient access to multiple data sources
- Support packaging and deploying new models or updated models to production
- Create the necessary infrastructure needed for model training
Requirements:
- Bachelor's Degree or higher in an Information Technology discipline or related field of study and minimum of two years of work experience designing, programming, and supporting software programs or applications
- In lieu of degree, minimum of four years related work experience designing, programming, and supporting software programs or applications may be accepted
- Data focused software engineer with experience integrating cloud services and resources (e.g., AWS - S3, EC2, Lambdas) and with ability to process large volumes of structured and unstructured data
- Experience with Unix/Shell scripting, Bash, Snowflake or Tecton, Terraform, Docker, highly proficient in Python and experience with one or more parallel computing and/or data manipulation tools (e.g., Prefect, Spark, SQL or related multiprocessing package)
- Deployment of machine learning models for real-time use cases and understanding of machine learning algorithms
- Experience designing and evaluating approaches to high volume real-time data streams
- CI/CD automation (e.g., GIT, GitHub actions, or Azure DevOps)