AWS Cloud ML Engineer

AWS Cloud Client Engineer Visa : Any Contract : W2 ( C2C ) Experience : 8 Location: Smithfield RI or Westlake Texas onsite 2 weeks per month starting Sept. 2024 (SMT is Highly preferred) Must Have Skills: AWS Cloud Development background, Terraform, Python Scripting Client / AI exp Preferred Skills: AWS SageMaker Hiring Manager Notes: Candidiates local /Relo ready to Smithfield RI are top Choice, Westlake TX will be reviewed later The Workplace Investing Data Engineering and Exchange AI Delivery Chapter team is looking for a Cloud / DevOps Engineer to join our team to help implement and enhance technical solutions for an intelligent unified answer platform product. This role is a dynamic agile engineering position where you will partner with our development team and peer data scientists. This role will be a great mix of Cloud, Devops, Data Engineering and lots of hands-on work partnering with our data scientists and business partners to design, develop and deploy full-stack AI search and process automation solutions. It is a great chance to work on an innovative agile development team to help build, innovative and deploy high business value AI powered solutions to improve life for our operations associates. The Expertise and Skills You Bring 3 to 5 years hands on development experience with AWS cloud provider. Experience working with AWS infrastructure (S3, CFTs, EC2, EKS, IAM). Experience in managing Cloud infrastructures like resource utilization, optimization and cost efficiency. Ability to collaborate with engineering and development teams to evaluate and provide optimal cloud solutions. Experience working with security, data, and AI pipeline technologies (RDS/Postgres, Snowflake, Airflow) and infrastructure as Code (Terraform, Python, Ansible, CFT). Experience in writing code (scripting) in languages such as Python, Groovy and Bash. Strong experience working with CI/CD processes and tools (Jenkins, Artifactory, Docker/Containers, Helm charts and Kubernetes). Experience with Machine Learning and model development lifecycle (AWS-Sagemaker) is highly preferred. Experience with logging, monitoring, and alerting using tools such as DataDog and Splunk is a plus. Bachelor's degree in computer science or other related discipline. The Team The team is an agile squad in the Intelligent Automation AI Product Area in Workplace Services. The squad intends to use cloud technologies and deploy solutions using all current software engineering principles. It's a great chance to work on an agile team to help build innovative and high business value AI powered solutions to improve tough manual operations activities.