JobRialto
DevOps/MLOps Engineer Lead
JobRialto, Findlay, Ohio, us, 45839
Position Summary
We are seeking an experienced and highly motivated DevOps / MLOps Engineer Lead to join our dynamic Data Science and AI team. In this role, you will be pivotal in creating and maintaining robust, scalable, and efficient CI/CD pipelines for our machine learning models and data processing workflows. You will collaborate with cross-functional teams to streamline and automate the end-to-end deployment processes, ensuring our AI/ML initiatives are delivered with high quality and speed.
Key Responsibilities
Develop and Implement CI/CD Pipelines: Design, build, and maintain continuous integration and deployment pipelines for machine learning models and data processing workflows.
Automation and Orchestration: Develop and continuously improve automation solutions to enable teams to build and deploy code efficiently and consistently.
Promote DevSecOps Principles: Foster a DevSecOps culture across the Analytics & Innovation organization, ensuring security is integrated into the development process.
Lifecycle Streamlining: Streamline the data science and development lifecycles by identifying and resolving pain points and productivity barriers.
Collaboration: Work closely with data scientists, data engineers, and software developers to integrate and deploy machine learning models into production.
Monitoring and Troubleshooting: Implement monitoring and logging solutions to ensure the health and performance of deployed models and systems, and troubleshoot issues as they arise.
Security and Compliance: Ensure the security and compliance of data and infrastructure, adhering to industry best practices and regulatory requirements.
Documentation: Maintain comprehensive documentation of systems, processes, and workflows to facilitate knowledge sharing and collaboration.
Desired Skills and Experience
Requirements:
Education: Bachelor's Degree in Computer Science, Engineering, or a related field.
Experience: 5+ years of experience in DevOps, MLOps, or a related field.
Azure DevOps and AzureML experience.
Technical Expertise:
Proficiency in cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Strong programming skills in Python, Bash, PowerShell or other scripting languages.
Experience with infrastructure as code (Terraform, ARM).
Tool Proficiency:
Familiarity with CI/CD tools (Jenkins, GitHub Actions, ADO Pipelines).
Knowledge of machine learning frameworks (TensorFlow, PyTorch) and data processing tools (Apache Spark, Airflow).
Problem-Solving: Excellent problem-solving and analytical skills, with a focus on delivering practical and efficient solutions.
Preferred Experiences:
Advanced Analytics Tools: Experience with advanced analytics tools and methodologies, including monitoring and logging solutions (Azure Monitor, Prometheus, Grafana).
Agile Methodologies: Experience working in Agile development environments.
Communication: Strong verbal and written communication skills, capable of articulating complex technical concepts to both technical and non-technical stakeholders.
Team Collaboration: A collaborative mindset with a track record of working effectively within diverse teams.
Other Qualifications:
AZ-400 DevOps Engineer Certification is desired.
Experience with Data Science and Machine Learning teams is desired.
Why Join Us:
Join our forward-thinking Data Science & AI team and play a critical role in advancing our AI/ML capabilities. Here's what you can expect:
Innovation: Be at the forefront of integrating cutting-edge DevOps and MLOps practices to streamline AI/ML operations.
Collaboration: Work alongside talented data scientists, ML engineers, and cloud experts in a fast-paced environment that fosters continuous learning and growth.
Impact: Make significant contributions to the company's success by enhancing the efficiency and scalability of our AI/ML initiatives.
Education:
Bachelors Degree
We are seeking an experienced and highly motivated DevOps / MLOps Engineer Lead to join our dynamic Data Science and AI team. In this role, you will be pivotal in creating and maintaining robust, scalable, and efficient CI/CD pipelines for our machine learning models and data processing workflows. You will collaborate with cross-functional teams to streamline and automate the end-to-end deployment processes, ensuring our AI/ML initiatives are delivered with high quality and speed.
Key Responsibilities
Develop and Implement CI/CD Pipelines: Design, build, and maintain continuous integration and deployment pipelines for machine learning models and data processing workflows.
Automation and Orchestration: Develop and continuously improve automation solutions to enable teams to build and deploy code efficiently and consistently.
Promote DevSecOps Principles: Foster a DevSecOps culture across the Analytics & Innovation organization, ensuring security is integrated into the development process.
Lifecycle Streamlining: Streamline the data science and development lifecycles by identifying and resolving pain points and productivity barriers.
Collaboration: Work closely with data scientists, data engineers, and software developers to integrate and deploy machine learning models into production.
Monitoring and Troubleshooting: Implement monitoring and logging solutions to ensure the health and performance of deployed models and systems, and troubleshoot issues as they arise.
Security and Compliance: Ensure the security and compliance of data and infrastructure, adhering to industry best practices and regulatory requirements.
Documentation: Maintain comprehensive documentation of systems, processes, and workflows to facilitate knowledge sharing and collaboration.
Desired Skills and Experience
Requirements:
Education: Bachelor's Degree in Computer Science, Engineering, or a related field.
Experience: 5+ years of experience in DevOps, MLOps, or a related field.
Azure DevOps and AzureML experience.
Technical Expertise:
Proficiency in cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Strong programming skills in Python, Bash, PowerShell or other scripting languages.
Experience with infrastructure as code (Terraform, ARM).
Tool Proficiency:
Familiarity with CI/CD tools (Jenkins, GitHub Actions, ADO Pipelines).
Knowledge of machine learning frameworks (TensorFlow, PyTorch) and data processing tools (Apache Spark, Airflow).
Problem-Solving: Excellent problem-solving and analytical skills, with a focus on delivering practical and efficient solutions.
Preferred Experiences:
Advanced Analytics Tools: Experience with advanced analytics tools and methodologies, including monitoring and logging solutions (Azure Monitor, Prometheus, Grafana).
Agile Methodologies: Experience working in Agile development environments.
Communication: Strong verbal and written communication skills, capable of articulating complex technical concepts to both technical and non-technical stakeholders.
Team Collaboration: A collaborative mindset with a track record of working effectively within diverse teams.
Other Qualifications:
AZ-400 DevOps Engineer Certification is desired.
Experience with Data Science and Machine Learning teams is desired.
Why Join Us:
Join our forward-thinking Data Science & AI team and play a critical role in advancing our AI/ML capabilities. Here's what you can expect:
Innovation: Be at the forefront of integrating cutting-edge DevOps and MLOps practices to streamline AI/ML operations.
Collaboration: Work alongside talented data scientists, ML engineers, and cloud experts in a fast-paced environment that fosters continuous learning and growth.
Impact: Make significant contributions to the company's success by enhancing the efficiency and scalability of our AI/ML initiatives.
Education:
Bachelors Degree