Agility Partners LLC
Jr. ML Ops Engineer Company Hidden Finance OH Contract-to-Hire Developer 1 Openi
Agility Partners LLC, Charleston, West Virginia, United States,
Agility Partners is seeking qualified applicants to fill an open Jr. ML Ops Engineer position with one of our Banking clients. This is a forward-thinking team within a large enterprise bank, deeply invested in leveraging machine learning and artificial intelligence to drive impactful business outcomes. The team is responsible for ensuring the smooth, scalable and secure deployment of machine learning models into production, handling both real-time and batch processing workloads. They offer a unique opportunity to work closely with data scientists and engineers, focusing on large language models and cutting-edge MLOps practices.Responsibilities
Manage and update Docker images, ensuring they are secure and optimized.Collaborate with data scientists to validate that models run effectively on updated images.Address security vulnerabilities by updating and patching Docker images.Deploy, manage, and scale AWS services (SageMaker, S3, Lambda) using Terraform.Automate the spin-up and spin-down of AWS infrastructure using Terraform scripts.Monitor and optimize AWS resources to ensure cost-effectiveness and efficiency.Design, implement, and maintain CI/CD pipelines in Azure DevOps (ADO).Integrate CI/CD practices with model deployment processes, ensuring smooth productionization of ML models.Participate in the end-to-end process of productionizing machine learning models, from model deployment to monitoring and maintaining their performance.Work with large language models, focusing on implementing near real-time and batch inferences.Address data drift and model drift in production environments.Work closely with data scientists, DevOps engineers, and other MLOps professionals to ensure seamless integration and deployment of ML models.Stay updated on the latest trends and technologies in MLOps, especially related to AWS and Docker.Benefits and Perks
This is a great opportunity to work for a mid-sized financial institution that is striving to be the bank of choice; one that focuses on its customers, not its competition. An organization that provides a dynamic, fulfilling work environment that is productive, collaborative and innovative.Highly visible team with a regional financial services company where your work matters and your accomplishments are recognized!Amazing opportunity for growth, healthy work/life balance and a community focused environment.Working for an organization that focuses on company culture, inclusion and diversity.On a team whose Core values that include: Can-Do Attitude, Service at Heart and Forward Thinking.50% medical coverage for you and your entire family.401(k).Paid Holidays.Life Insurance.Disability coverage.The Ideal Candidate
The ideal candidate would bring the following:Python: Deep expertise in Python for scripting and automation.AWS: Strong experience with AWS services, particularly SageMaker, S3, and Lambda.Terraform: Proficiency in using Terraform for infrastructure-as-code on AWS.Docker: Extensive experience with Docker, including building, managing, and securing Docker images.Linux: Strong command-line skills in Linux, especially for Docker and system management.DevOps Experience: Azure DevOps (ADO): Significant experience in setting up and managing CI/CD pipelines in ADO.Git: Proficient in using Git for version control and collaboration.Additional DevOps Tools: Experience with Jenkins or other CI/CD tools is a plus.Experience & Education: 4 years of experience in combination of MLOps/DevOps/Data Engineering; Bachelor's degree in Computer Science, Engineering, or a related discipline.Preferred Qualifications:Experience with large language models and productionizing ML models in a cloud environment.Exposure to near real-time inference systems and batch processing in ML.Familiarity with data drift and model drift management.
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Manage and update Docker images, ensuring they are secure and optimized.Collaborate with data scientists to validate that models run effectively on updated images.Address security vulnerabilities by updating and patching Docker images.Deploy, manage, and scale AWS services (SageMaker, S3, Lambda) using Terraform.Automate the spin-up and spin-down of AWS infrastructure using Terraform scripts.Monitor and optimize AWS resources to ensure cost-effectiveness and efficiency.Design, implement, and maintain CI/CD pipelines in Azure DevOps (ADO).Integrate CI/CD practices with model deployment processes, ensuring smooth productionization of ML models.Participate in the end-to-end process of productionizing machine learning models, from model deployment to monitoring and maintaining their performance.Work with large language models, focusing on implementing near real-time and batch inferences.Address data drift and model drift in production environments.Work closely with data scientists, DevOps engineers, and other MLOps professionals to ensure seamless integration and deployment of ML models.Stay updated on the latest trends and technologies in MLOps, especially related to AWS and Docker.Benefits and Perks
This is a great opportunity to work for a mid-sized financial institution that is striving to be the bank of choice; one that focuses on its customers, not its competition. An organization that provides a dynamic, fulfilling work environment that is productive, collaborative and innovative.Highly visible team with a regional financial services company where your work matters and your accomplishments are recognized!Amazing opportunity for growth, healthy work/life balance and a community focused environment.Working for an organization that focuses on company culture, inclusion and diversity.On a team whose Core values that include: Can-Do Attitude, Service at Heart and Forward Thinking.50% medical coverage for you and your entire family.401(k).Paid Holidays.Life Insurance.Disability coverage.The Ideal Candidate
The ideal candidate would bring the following:Python: Deep expertise in Python for scripting and automation.AWS: Strong experience with AWS services, particularly SageMaker, S3, and Lambda.Terraform: Proficiency in using Terraform for infrastructure-as-code on AWS.Docker: Extensive experience with Docker, including building, managing, and securing Docker images.Linux: Strong command-line skills in Linux, especially for Docker and system management.DevOps Experience: Azure DevOps (ADO): Significant experience in setting up and managing CI/CD pipelines in ADO.Git: Proficient in using Git for version control and collaboration.Additional DevOps Tools: Experience with Jenkins or other CI/CD tools is a plus.Experience & Education: 4 years of experience in combination of MLOps/DevOps/Data Engineering; Bachelor's degree in Computer Science, Engineering, or a related discipline.Preferred Qualifications:Experience with large language models and productionizing ML models in a cloud environment.Exposure to near real-time inference systems and batch processing in ML.Familiarity with data drift and model drift management.
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