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Machine Learning Engineer
Confirmed live in the last 24 hours
Austin, TX, USA
Experience Level
Desired Skills
Data Science
Development Operations (DevOps)
  • 2+ years of experience in a data engineering, software engineering, DevOps, or similar role
  • 2+ years of experience developing in Python and SQL
  • 1+ years of experience working on or supporting data science projects
  • Understanding of data science terminology and the ability to communicate with Data Scientists on highly technical machine learning projects
  • Understanding of the machine learning lifecycle development and deployment process
  • Experience managing infrastructure of machine learning platforms or systems running operational machine learning models
  • Understanding of common data architectures, processes, and paradigms such as data warehousing/modeling, ETL/ELT, feature engineering, batch vs streaming pipelines
  • Ability to articulate, diagram, and document technical data science and engineering concepts
  • Experience with industry-standard Data and Machine Learning Platform technologies such as data warehouses, workflow orchestration platforms, database replication platforms, data quality frameworks, feature stores, data science notebooking tools, etc
  • Experience or familiarity working in agile frameworks
  • Work with a team of Machine Learning Engineers to execute on roadmap items and strategic initiatives for Machine Learning Platform components and capabilities
  • Deploy and monitor infrastructure supporting our machine learning model deployments and development environments
  • Build batch and real-time pipelines for feature engineering and understand when to use each implementation
  • Facilitate machine learning model deployments through different environments and coordinate dependencies across Data Science, Data Engineering, and Product Engineering teams
  • Implement and document team standards and machine learning operations (MLOps) best practices that have a broad impact on Data and Engineering teams
  • Execute on strategies for reducing the gap between building models in a development environment and running them in production
  • Implement monitoring and alerting frameworks to ensure data quality in our feature engineering pipelines and machine learning deployments
  • Develop Python libraries, functions, and other shared components that enable easier sharing of resources across many Data Science teammates and machine learning models
Arrive Logistics

1,001-5,000 employees

Carrier and customer-centric logistics company
Company Overview
Arrive Logistics is defining a new standard for experience in freight, pushing the limits of what's possible for themselves and their partners every day.
  • Uncapped earning potential
  • Matching 401(k)
  • World class training program
  • Nationally recognized company culture
  • Incredible sales contests