Jr. MLOps Engineer

For over 30 years, Midwest Tape has served libraries and their patrons with unparalleled access to the best content available in the media world. Our digital offering, hoopla Digital, combines the media and library expertise of Midwest Tape with the latest in web and mobile technology, delivering an all-in-one experience to the library world. As hoopla continues to grow on a global scale, we are expanding our team.

At Midwest Tape, we know our people are the reason for our success. We value our employees and believe in empowering them to help them thrive. We offer competitive pay and benefits, a healthy work/life balance, and appreciation for a job well done.

Benefits:

• Medical, dental, & vision insurance
• 401k + match
• Profit sharing
• Paid vacation and personal time
• Flex time
• 10 paid holidays
• Company performance bonus
• Holiday bonus
• Training & career development opportunities

Position Summary:

As a Junior MLOps Engineer at Midwest Tape, you will play a critical role in supporting the machine learning and data science team by ensuring the smooth and efficient deployment, monitoring, and management of machine learning models and data pipelines. You will work in a collaborative environment, leveraging cutting-edge technologies and tools to bridge the gap between development and operations, enabling the seamless execution of AI solutions.

Primary Duties and Responsibilities:

1. Collaborate with data scientists and machine learning engineers to deploy machine learning models into production environments.
2. Understand data requirements and data model needs of a project and help shape data to meet requirements.
3. Manage and monitor the infrastructure and resources required for running machine learning workloads.
4. Build and maintain CI/CD pipelines for ML model development and deployment.
5. Collaborate with data engineers to ensure data pipelines are reliable and scalable.
6. Implement data validation and quality checks to ensure the integrity and accuracy of data used in machine learning processes.
7. Implement robust monitoring and alerting systems to proactively identify and address issues in the ML environment.
8. Maintain comprehensive documentation for deployment processes, system configurations, and best practices.
9. Implement security best practices to protect sensitive data and ensure compliance with data privacy regulations.

Skills:

• Basic knowledge of machine learning concepts and methodologies.
• Proficiency in scripting and programming languages (e.g., Python, Bash).
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Preferred Education Requirements:

Preferred Experience:

• 0-2 Years of experience
• Previous experience with MLOps tools and frameworks
• Experience working with Linux OS is required
• Knowledge of cloud computing platforms (e.g., AWS).
• Experience with CI/CD tools (e.g., Jenkins).
• Familiarity with containerization technologies (e.g., Docker) and container orchestration (e.g., Kubernetes).

Physical Requirements / Work Environment:

The work environment characteristics and physical demands described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Ability to regularly sit for extended periods of time.
• Perform repetitive motion-type tasks
• Must be physically present for meetings, presentations, and training.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.