ML Ops Engineer/Full-Stack AWS ML Engineer

Role: ML Ops Platform EngineerLocation: Reston, VA (Onsite)Duration: Long termRequired Qualifications 3+ years of hands-on experience with AWS services, including EKS, EC2, S3, IAM, CloudWatch, and ECR. Strong experience operating and troubleshooting Kubernetes (preferably AWS EKS). Proficiency in containerization (Docker) and orchestration concepts. Strong programming/scripting experience in Python and Bash. Experience building and managing CI/CD pipelines (GitLab or equivalent). Familiar

ML Engineer - AWS, Machine Learning, SageMaker, Git, Terraform, MLOps Type: W2 With Benefits - No C2C Location: Washington DC - 2 or 3 days per week onsite Key Responsibilities Build and operationalize ML models using AWS SageMaker. Work closely with: Data Science team on model development and operationalization. Technology team to validate platform integration and functionality. Act in a product owner like capacity for the ML Ops platform ensuring alignment with model development needs. Validat

Top 5 Technical Skills: MLOpsPythonAWS (SageMaker, S3, EC2, EKS/Fargate, Lambda, AWS Glue, and IAM)Docker/TerraformCICDRequired Skills and Qualifications 15+ years of overall exepreince - Proven experience (6+ years preferred) in MLOps, DevOps, or a related role, with hands-on experience in developing and deploying ML applications at scale.Programming Proficiency: Strong proficiency in Python and relevant ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).AWS Expertise: In-depth e

Role: AI/ML Engineer - Python & AWS Location- Reston, VA Duration: Fulltime/Contract Onsite: 5 Days Onsite Job Description: Core Responsibilities (AI/ML, Python, AWS, GenAI)Design and implement end-to-end AI/ML and Generative AI solutions using Python, including model training, evaluation, optimization, and deployment.Build and maintain cloud native applications on AWS using services such as Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.Develop high performan