Machine Learning Ops Engineer

Added: 9/7/2021

REF: 14149

Contract: Permanent

Location: New York, United States

About Us

We are a non profit political strategy group that is aiming to disrupt the politics of education. We want to make sure that every child is able to have equal access to high level, equitable public schooling.

We encourage campaigns and campaign organizers to engage communities in order to push for improvements to be made to public schools.

Who We Are

We are made up of innovators in strategy, analytics, data, and AI. We are a diverse group of former teachers, political campaigners, data scientists, and more. We are searching for people who have a passion for helping improve how we work and realize the vision of our organization. 

About the Position

We are searching for a talented Machine Learning Ops Engineer who would work along side our data engineering and data science teams. You would be tasked with designing and implementing the machine learning infrastructure that would be used to deploy machine learning models in production, quickly and at scale. We use a wide range of database technologies: (AWS Redshift, mongoDB, Snowflake) and tools: (AWS EC2, AWS S3, Python, Airflow). This role would report to the Lead Data Engineer. 

Key Responsibilities

  • Build and manage end to end ML pipelines that can power the full range of ML capabilities of our data science team. 
  • Ensure data quality every stage of acquisition and processing. This includes such areas as data collection, normalization, and transformation. 
  • Create new solutions to enable stakeholders to understand our data more intuitively. 
  • Stay current with ML tools in political and educational domains
  • Function as the Machine Learning expert. Including being able to create solutions design and implementation decisions. 


  • MS in CS preferred, or equivalent experience in ML, CS, statistics, applied math, etc. 
  • 4+ years designing systems at scale
  • 4+ years of experience with data infrastructure (AWS and Snowflake)
  • 3+ years of experience developing data pipelines, and executing deployment of various Machine Learning models, (Kubernetes)
  • 2+ years of experience in using Machine Learning platforms for the ongoing development and deployment of models
  • Experience in the evaluation and implementation of a Machine Learning platform solution (i.e. Domino, MLflow or Databricks)
  • Skilled in programming languages like Python, Java/C++/C# and SQL
  • Sound knowledge in dealing with large data sets for analytical approach and quantitative methods
  • Experience in the consideration and implications of security expectations around our machine learning model process and infrastructure
  • Solid understanding of machine learning fundamentals, and familiar with standard algorithms and techniques
  • Ability to analyze a wide variety of data: structured and unstructured, observational and experimental, to drive system designs, data models and product implementations
  • Good understanding of cloud computing and infrastructure concepts


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