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Senior AI/ML Platform Engineer

Newark, NJ
Job Description:

The AI/ML Engineering team is looking for a Senior AI/ML Platform Engineer to join a diverse team dedicated to providing best-in-class data services to our customers, stakeholders, and partners. This is a contract to hire role so mucs be GC or US Citizen

As a part of our organization, you will work with our Data Science and BUs to define solutions for institutionalizing data-driven decision-making in a cost-effective and scalable manner. The focus is on driving analytical outcomes and impacting the Machine Learning and AI ecosystem. The Senior AI/ML Platform Engineer with experience in AI/ML platforms such as AWS SageMaker.

  • Focus on optimizing existing systems, building infrastructure, and eliminating work through automation.
  • Influence application and security architecture and design across multi and hybrid cloud platforms.
  • Peer-reviewing infrastructure-as-code (AWS CloudFormation, Python, Terraform, or similar).
  • Partnering with application and infrastructure teams to develop reusable cloud patterns.
  • Deployment and troubleshooting of infrastructure code.
  • Partner with the Site Reliability Engineering (SRE) team to conduct post-incident reviews and root cause analysis and building monitoring and automation to prevent future incidents.
  • Identify opportunities to build self-service capabilities and automate infrastructure and application deployments.
  • Develop tools and best practices for platform development, developer productivity, automation (MLOps, CI/CD, A/B testing), and production operations.
  • Design, Develop & deliver critical components, frameworks, services, and products using AWS SageMaker, Lambda, and container technologies in AWS.
  • Develop processes, model monitoring, and governance framework for successful ML model operationalization.
  • Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations.
  • Assist in gathering and analyzing non-functional requirements and translating that into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture

Technical Qualifications:
  • The cloud is a rapidly changing world, with the major players announcing new features almost on a daily basis. A successful Cloud Engineer doesn’t need to know everything about everything but instead keeps a pulse on new developments and emerging paradigms to identify areas where they can continuously improve their skill sets.
  • Ability to debug, optimize code, and automate routine tasks.
  • A systematic problem-solving approach coupled with a strong sense of ownership and drive.
  • Ability to quickly pickup and understand where newly released cloud services would be appropriate for business applications.
  • Experience with infrastructure automation tools such as Puppet, Ansible, CloudFormation, or Terraform.
  • Working knowledge of pipeline-automation tools such as Jenkins, CodePipeline, Azure DevOps, or other comparable tools.
  • Experience using Git for source control management.
  • Ability to proficiently write code in Python, Node.js, Bash (shell), PowerShell, or other similar languages.
  • Experience using Docker within container orchestration platforms such as AWS ECS, EKS, Google Anthos, or others.
  • Comfortable in a Linux environment.
  • Understanding of foundational AWS services such as VPCs, EC2, S3, RDS, Auto Scaling Groups, CloudWatch Logs, etc.
  • In-depth knowledge of security and IAM within AWS, including the management and operation of Security Groups, KMS Keys, VPC NACLs, and SCPs.
  • Familiar with ETL and big data tool-chains such as those provided by Hadoop/EMR, Glue, Spark, Impala, or similar.
  • Understanding of relational database systems and how applications interact with them.
  • Familiarity with one or more log and event aggregation and monitoring systems such as Splunk, Elasticsearch (ELK), Prometheus, Grafana, or similar.

  • 5+ years’ experience in Amazon Web Services (AWS).
  • Experience in working in an Agile/Scrum-focused organization.
  • Strong verbal and written communication skills; comfortable with translating technical problems to non-technical audiences.
  • MS/BS degree in Information Technology, Computer Science, related technical field, or equivalent practical experience.

Preferred Qualifications:
  • One or more Associate or Professional-level AWS certificates.
  • Prior experience within a DevOps, DevSecOps, SRE, or UNIX/Linux Sys-Admin teams.


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