QA Engineering Lead

About Fusemachines Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 400 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world. Position Overview We are seeking an experienced QA Engineering Lead with a background in testing machine learning (ML) web applications to join our team. Bonus: If you have worked with LLM's. The ideal candidate will lead the quality assurance efforts with a very hands-on attitude for our ML-driven projects, ensuring the highest standards of quality and reliability are met. The QA Engineering Lead will collaborate closely with cross-functional teams, mentor junior QA engineers, and drive the adoption of best practices in ML Application testing methodologies. This is a remote, contract position. Responsibilities

• Lead the QA team in developing and implementing comprehensive test plans, test cases, and strategies specific to machine learning applications.
• Drive the adoption of automated testing tools and frameworks to increase testing efficiency and coverage.
• Create strategies and tests for new product features, in addition to executing regression testing of existing features.
• Work with development teams to develop test plans, test suites, and test cases to ensure that the software stack is thoroughly verified and validated through manual and automated methods.
• Submit, track, and verify defects through the software development lifecycle, ensuring timely resolution.
• Write documents, tests, scripts, and tools to help facilitate testing and improve efficiency.
• Define and establish QA metrics, measuring the effectiveness of testing processes and identifying areas for improvement.
• Collaborate with product owners, machine learning engineers, and software engineers to ensure alignment on quality objectives and priorities.
• Design and execute testing for ML models, including functional, performance, and scalability testing.
• Mentor and provide guidance to junior QA engineers on testing methodologies and best practices.
• Stay current with industry trends and advancements in ML testing techniques and tools.
• Participate in release planning and deployment activities for ML-driven features, ensuring smooth integration and deployment.
• Investigate and troubleshoot issues related to ML model performance or behavior, working closely with data scientists and engineers to resolve them.
• Conduct functional, regression, performance, and security testing as needed.
• Drive the adoption of automated testing tools and frameworks to increase testing efficiency and coverage.
• Define and establish QA metrics to measure the effectiveness of testing processes and identify areas for improvement.
• Participate in release planning and deployment activities, ensuring a smooth and successful release process.
• Investigate and troubleshoot issues reported by customers or internal stakeholders, identifying root causes and driving resolution.

• Bachelor's degree in Computer Science, Engineering, or related field; or equivalent work experience.
• 5 years of experience in quality assurance or software testing, with a some experience working on machine learning applications.
• Familiarity with basic machine learning concepts
• Familiarity in programming languages commonly used in ML development (e.g., Python, R, etc.).
• Experience in designing and implementing effective test strategies for ML models including LLM's
• Excellent analytical and problem-solving skills, with a keen attention to detail.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Experience with Agile development methodologies is preferred.
• Familiarity with LLM evaluation frameworks
• Hands-on experience with automated testing tools and frameworks (e.g., Selenium, JUnit, TestNG, etc.).