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ML (Machine Learning) Engineer

ITR Group

St Paul · Hybrid Senior $60 – $85/hr Today

About the role

About

Long term contract to potential hire opportunity for an experienced Machine Learning Engineer.
Hands‑on ML Engineering Consultant with strong technical depth and proven AI experience. This role designs, builds, and deploys scalable machine learning solutions in AWS, working closely with cross‑functional teams. Ideal candidates are highly collaborative and genuinely enjoy being onsite as part of a team.

Requirements

  • Must be local to St Paul, MN area (will be onsite 2-3 days/week)
  • Work authorization status: US Citizen or GC holder

Responsibilities

  • Design, build, and deploy scalable ML pipelines and AI solutions
  • Develop and productionize models using AWS tools and modern ML frameworks
  • Collaborate with data scientists, engineers, and business stakeholders
  • Implement CI/CD, DevOps, and MLOps best practices
  • Optimize models and pipelines for performance, reliability, and scale
  • Support end-to-end delivery: data, modeling, deployment, and monitoring

Must‑Have Skills

  • Strong technical foundation (Python, Advanced SQL)
  • Proven AI/ML experience in production environments
  • AWS expertise (SageMaker, Bedrock, EKS/Kubernetes, Step Functions)
  • Experience with Airflow and ML pipeline orchestration
  • CI/CD, DevOps, and infrastructure as code (Terraform, CloudFormation, etc.)
  • Docker and containerized deployments
  • MLOps and model lifecycle management

Nice to Have

  • Apache Kafka
  • MLflow
  • StreamSets

Qualifications

  • 5+ years of ML engineering or similar experience
  • Experience building and deploying ML solutions at scale
  • Strong collaboration and communication skills
  • Comfortable working in agile, fast‑paced environments
  • Must be enthusiastic about working onsite 2–3 days per week

Compensation & Benefits

ITR Group offers a competitive compensation and benefits package, including medical, dental, and 401(k) for eligible employees. The W2 pay range for this type of role is approximately $60.00‑85.00 per billable hour. This range is an estimate and not a guarantee of compensation. The final rate will be determined by factors such as experience, market trends, and specific job assignments. Discover more about how ITR Group connects top talent with leading client opportunities.

Requirements

  • Must be local to St Paul, MN area (will be onsite 2-3 days/week)
  • Work authorization status: US Citizen or GC holder
  • Hands-on ML Engineering Consultant with strong technical depth and proven AI experience
  • Strong technical foundation (Python, Advanced SQL)
  • Proven AI/ML experience in production environments
  • AWS expertise (SageMaker, Bedrock, EKS/Kubernetes, Step Functions)
  • Experience with Airflow and ML pipeline orchestration
  • CI/CD, DevOps, and infrastructure as code (Terraform, CloudFormation, etc.)
  • Docker and containerized deployments
  • MLOps and model lifecycle management
  • Apache Kafka
  • 5+ years of ML engineering or similar experience
  • Experience building and deploying ML solutions at scale
  • Strong collaboration and communication skills
  • Comfortable working in agile, fast-paced environments
  • Must be enthusiastic about working onsite 2–3 days per week

Responsibilities

  • This role designs, builds, and deploys scalable machine learning solutions in AWS, working closely with cross-functional teams
  • Ideal candidates are highly collaborative and genuinely enjoy being onsite as part of a team
  • Design, build, and deploy scalable ML pipelines and AI solutions
  • Develop and productionize models using AWS tools and modern ML frameworks
  • Collaborate with data scientists, engineers, and business stakeholders
  • Implement CI/CD, DevOps, and MLOps best practices
  • Optimize models and pipelines for performance, reliability, and scale
  • Support end-to-end delivery: data, modeling, deployment, and monitoring

Benefits

health_insurancedental_coverage

Skills

AWSAWS CloudFormationAWS EKSAWS SageMakerAWS Step FunctionsAirflowApache KafkaDockerKubernetesMLflowMLOpsPythonSQLStreamSetsTerraform

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