Job Summary Our client, a leading Financial Services provider, is seeking a Sr. ML Ops Engineer to support the deployment, automation, and operational management of machine learning solutions within AWS environments. This role will own the end-to-end ML deployment lifecycle, partnering with cross-functional teams to deliver scalable, secure, and reliable production AI solutions.Contract detailsContract type and duration: 12 Month contract -potential to convert
Location: USAWork Model: RemoteCore ResponsibilitiesDeploy, configure, and maintain machine learning solutions within AWS environments, ensuring reliable integration into production applicationsOwn the end-to-end ML deployment lifecycle, including model onboarding, infrastructure setup, deployment, validation, and operational supportDesign, implement, and document AWS architectures that support scalable, secure, and high-performing ML workloadsConfigure and manage AWS services required for model hosting, application connectivity, monitoring, and performance optimizationCollaborate with application, data, and engineering teams to enable seamless consumption of deployed ML modelsMonitor production ML solutions, troubleshoot issues, and implement improvements to ensure availability and performanceSupport the establishment of scalable engineering practices and deployment standards within a growing AI organizationPartner with cross-functional stakeholders to evaluate requirements, recommend technical solutions, and drive successful ML implementations Required Skills/Experience (Must-Haves)Proven hands-on experience personally deploying and supporting machine learning models in production AWS environmentsStrong experience with AWS services, particularly SageMaker, Lambda, API Gateway, and CloudWatchHands-on Terraform experience provisioning and managing AWS infrastructureExperience building or maintaining CI/CD pipelines for machine learning or cloud application deploymentsUnderstanding of model packaging, hosting, inference endpoints, and application integrationExperience troubleshooting production systems and supporting deployed ML applicationsKnowledge of AWS networking, IAM, VPC configurations, and enterprise security requirementsStrong software engineering fundamentals and experience collaborating with cloud and platform engineering teamsAbility to communicate technical concepts, explain architectural decisions, and document solutionsExperience working within large enterprise environments with established security and infrastructure controlsPreferred Skills/Experience (Nice-to-Haves)AWS or Terraform certifications5+ years in software, cloud, or data engineering2+ years deploying ML solutions in AWSDocker containerization and Amazon ECR experienceExperience with SageMaker Model Registry, Model Monitor, and model versioningFamiliarity with blue/green, canary, or other controlled deployment strategiesExperience optimizing AWS infrastructure for scalability, reliability, and costExperience creating reusable MLOps templates or deployment frameworksExposure to LLM integration within production ML workflowsCompensation & BenefitsPay Range: The approximate pay range for this position is between $189,000 and $270,000.
Please note that the pay range provided is a good faith estimate. Final compensation may vary based on factors including but not limited to background, knowledge, skills, and location. We comply with local wage minimums.Medical, Dental, & Vision Insurance PlansEmployee-Owned Profit Sharing (ESOP)401K offeredAbout KellyMitchell At KellyMitchell, our culture is world class. We’re movers and shakers! We don’t mind a bit of friendly competition, and we reward hard work with unlimited potential for growth. This is an exciting opportunity to join a company known for innovative solutions and unsurpassed customer service. We're passionate about helping companies solve their biggest IT staffing & project solutions challenges. As an employee-owned, women-led organization serving Fortune 500 companies nationwide, we deliver expert service at a moment's notice.Marketing Disclosure By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from KellyMitchell and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at https://www.careers.kellymitchell.com/privacy-policy. [143525]