DevOps/MLOps Engineer Lead

3 weeks ago

San Antonio, United States TEK NINJAS Full time

Job Description


Job Title:

DevOps / MLOps Engineer Lead

Location:

San Antonio, TX | Findlay, OH

Education Level:

Bachelor’s Degree

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.

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