Remote Machine Learning Engineer Jobs in Tavares, FL

WORKING AT THE MLC

The MLC is committed to excellence, service, transparency, and diversity. Our culture is collaborative, our people are adaptable. On our team, you are respected, valued for your unique strengths and experiences, and empowered to identify and resolve your own challenges.

The Mechanical Licensing Collective (The MLC) is a nonprofit organization designated by the U.S. Copyright Office to administer blanket mechanical licenses for digital music services in the United States. Our mission is to ensure that songwriters, composers, and music publishers are accurately paid for the use of their music in the digital ecosystem. While our foundation is rooted in music licensing and rights administration, the scale and complexity of the data we process-billions of usage records from digital service providers-has positioned The MLC at the intersection of music and technology. As we continue to build and refine the systems that power matching, royalty processing, and rights management, we are increasingly operating like a technology company, developing sophisticated platforms, data infrastructure, and automation to support the future of digital music licensing.

THE ROLE

As a Quality Assurance Engineer, you will design, implement, and own the testing strategy for the Matching Platform. You will build and maintain automated testing frameworks and perform exploratory validation across workflows, APIs, integrations, and user-facing components to ensure the system behaves as intended and that changes do not introduce regressions. You will contribute production-quality testing code, establish testing standards and best practices, and work closely with the Matching Team throughout story refinement and implementation to ensure new functionality is testable, clearly defined, and validated before completion. The Matching Platform is a critical tool that enables The MLC to drive accurate royalty payments to our Members.

This is a Remote position with preference for candidates located in either EST or CST.

QUALIFICATIONS

• Minimum five (5) years' experience in Quality Assurance or Quality Engineering within a software engineering team.
• Strong experience designing and implementing automated tests; able to write and maintain production-quality testing code.
• Hands-on experience with manual and exploratory testing in complex systems; able to validate behavior against business rules.
• Experience testing APIs and workflow-heavy or data-driven systems; proficient in SQL; experience working within AWS environments.
• Experience testing machine learning or probabilistic systems, building testing frameworks from scratch, or working with orchestration tools such as Dagster or Airflow is a plus.
• Strong attention to detail, clear documentation skills, and effective collaboration within Agile, cross-functional teams.
• Working proficiency in Python, familiarity with other languages is a plus.

ESSENTIAL RESPONSIBILITIES

AS A QA ENGINEER AT THE MLC, YOU WILL:

• Own the testing strategy for the Matching Platform, ensuring consistent validation across workflows, APIs, integrations, and user-facing components.
• Design, build, and maintain automated test suites in Python, establishing and evolving the team's testing framework.
• Perform manual and exploratory testing before work is considered complete, validating complex workflows, identifying defects, edge cases, unintended behaviors, and deviations from business rules.
• Collaborate closely with engineers and product stakeholders during story refinement and development to ensure features are testable and clearly defined.
• Define and maintain QA standards and testing practices within the Matching Team, contributing to regression coverage as the platform evolves.
• Investigate and document defects clearly, working with developers to resolve issues prior to ticket completion.

AS A MEMBER OF THE TECHNOLOGY TEAM, YOU WILL:

• Advocate for quality throughout the development lifecycle, partnering with engineers to incorporate testing considerations early.
• Contribute to the evolution of scalable, automated QA practices across the Technology organization.
• Promote consistent standards for reliability, validation, and defect management.
• Participate in Agile ceremonies, providing a quality-focused perspective in planning and retrospectives.
• Support continuous improvement of engineering practices as systems grow in complexity.