Python AWS Developer

Overview

On Site
$50 - $55
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

python
aw
sagemaker
mlops

Job Details

Role: Python AWS Developer
Location: Austin TX/ Sandiego CA/Onsite
Need Passport Number
We are looking for a highly skilled Python AWS Developer with expertise in Amazon SageMaker and MLOps practices to join our team. The ideal candidate will be responsible for developing and deploying scalable machine learning solutions on AWS, building robust MLOps pipelines, and collaborating with data science and DevOps teams to ensure smooth delivery of ML models in production.
Key Responsibilities
  • Develop scalable and efficient Python applications to support ML workflows.
  • Design, develop, and deploy ML models using Amazon SageMaker.
  • Implement end-to-end MLOps pipelines using services such as AWS CodePipeline, CodeBuild, Step Functions, and Lambda.
  • Automate data preprocessing, model training, evaluation, and deployment.
  • Integrate CI/CD for ML models in production environments.
  • Collaborate with data scientists, DevOps, and software engineering teams to improve model delivery lifecycle.
  • Monitor and manage model performance, drift, and retraining pipelines.
  • Optimize AWS infrastructure cost and performance for ML workflows.
Required Skills & Qualifications
  • Strong hands-on experience with Python programming (APIs, data handling, etc.).
  • Proven experience working with Amazon SageMaker for training and deploying ML models.
  • Solid understanding of AWS services such as S3, Lambda, ECS/EKS, CloudWatch, IAM, CloudFormation or Terraform.
  • Proficiency in building MLOps pipelines and using tools like MLflow, Kubeflow, Airflow, or Jenkins.
  • Experience in containerization (Docker) and orchestration (Kubernetes is a plus).
  • Familiarity with DevOps practices and Infrastructure-as-Code (IaC).
  • Experience with data versioning and model registry systems.
  • Understanding of ML lifecycle (training, validation, tuning, deployment, and monitoring).
Preferred Qualifications
  • AWS certification (e.g., AWS Certified Machine Learning Specialty).
  • Experience in deep learning frameworks (TensorFlow, PyTorch).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.