Machine Learning Operations Architect

5 days ago

New York, New York, United States Yieldmo Full time
Job Overview

Yieldmo is seeking an experienced Machine Learning Operations Architect to spearhead our ML initiatives. As a key member of our team, you will design and implement systems to support our data science efforts in a high-volume production environment.

Key Responsibilities:

  • Architect and deploy a software framework to securely handle data science workflows in production-grade environments
  • Facilitate seamless integration of ML models into operational pipelines between engineering and data science
  • Design and implement scalable, efficient ML pipelines on AWS and GCP
  • Design and implement CI/CD pipelines to automate the continuous integration and delivery of ML models
  • Monitor the performance of ML models and implement improvements
  • Ensure high availability and fault tolerance of the ML infrastructure
  • Optimize the performance and cost-efficiency of ML systems
  • Perform code reviews and maintain ML ops and engineering best practices

Requirements

We are looking for a highly skilled individual with:

  • 5+ years of experience with AWS or GCP
  • 10+ years of experience in software development with Python in a production environment focused on ETL, ML, and pipeline work
  • 10+ years of experience working with large datasets
  • 5+ years of experience working as a data scientist with technologies such as scikit-learn, R, SQL, H2O, Vertex AI, AWS Sagemaker, TensorFlow, PyTorch, and Spark
  • Comfortable building machine learning models on sparse datasets with high dimensionality
  • 5+ years with predictive analytics and developing optimization algorithms
  • Deep understanding of development and deployment processes with technologies including GitHub actions, containerization using Docker, and cloud services such as ECR/ECS, Lambda, and Cloudwatch
  • Experience working with Airflow or another workflow orchestration tool
  • Expert-level understanding of SQL in Snowflake and MySQL environments
  • Experience with high-performance SQL-based analytics data warehouses such as Snowflake, BigQuery, Redshift, Vertica, or Netezza
  • MS or equivalent combination of education and experience in Computer Science, Engineering, Information Systems, or quantitative science (Physics, Math, Computational Biology, Operations Research, etc.)
  • Strong verbal and written communication skills
  • Ad tech experience (SSPs, DSPs, Analytics, DMPs, CDPs)

Perks

We offer a fully remote workplace, generous employer contribution to Health Benefit premiums & 401k Match, work/life balance, flexible PTO, competitive compensation packages, Summer Fridays, and a generous learning stipend.

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