Demo

Machine Learning Engineer

IMCS Group
Chicago, IL Contractor
POSTED ON 3/27/2025
AVAILABLE BEFORE 4/25/2025

Job Title – Sr Machine Learning Engineer

Duration – 9 Months

Location – Chicago, IL

Only W2 (No C2C)

Job Description Summary

As a Senior Machine Learning Engineer, you will be responsible for developing and testing algorithms, conducting data analysis, and delivering actionable results to the business unit. Utilizing AWS Sagemaker technologies, you will build, test, and maintain ML Ops pipelines to ensure our machine learning models are effectively deployed and operational in production. This role involves creating and validating ML models, performing data transformations, and managing data repositories. Your contributions will support the long-term corporate analytics strategy and drive data-driven decision-making across the organization.

Duties:

  • Collaborate with data scientists, software engineers, and DevOps teams to develop and deploy ML models
  • Build, test, and deploy ML Ops pipelines on AWS
  • Manage and monitor production ML systems to ensure optimal performance, reliability, and scalability
  • Design and implement automated workflows for data cleaning, feature engineering, model training, and model deployment
  • Develop and maintain documentation for ML Ops processes and procedures
  • Continuously improve ML Ops pipeline performance and efficiency
  • Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure

Requirements:

  • Bachelor's or master's degree in computer science, Engineering, or a related field
  • Minimum of 5-7 years of experience in ML Ops, DevOps, or related roles
  • Strong knowledge of AWS services and tools related to ML Ops, such as SageMaker, Step Functions, Lambda, and CloudFormation
  • Hands-on experience building and deploying ML models in production using AWS
  • Proficiency in Python and/or other programming languages commonly used in ML, such as R, Java, or Scala
  • Familiarity with containerization technologies such as Docker and Kubernetes
  • Excellent problem-solving skills and attention to detail
  • Ability to work independently as well as in a team environment
  • Strong communication skills and ability to explain technical concepts to non-technical stakeholders

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