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QA Engineering Lead

Fuse MachinesNew York, NY

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Overview

Schedule
Full-time
Career level
Director
Remote
Hybrid remote
Benefits
Career Development

Job Description

About Fusemachines

Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to 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.

  • Hybrid. Must be able to meet in Hicksvile, Long Island twice a week*

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.

Qualifications:

  • 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.).

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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FAQs About QA Engineering Lead Jobs at Fuse Machines

What is the work location for this position at Fuse Machines?
This job at Fuse Machines is located in New York, NY, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Fuse Machines?
Employer has not shared pay details for this role.
What employment applies to this position at Fuse Machines?
Fuse Machines lists this role as a Full-time position.
What experience level is required for this role at Fuse Machines?
Fuse Machines is looking for a candidate with "Director" experience level.
What benefits are offered by Fuse Machines for this role?
Fuse Machines offers Career Development for this position. Actual benefits may vary depending on the employer's policies and employment terms.
What is the process to apply for this position at Fuse Machines?
You can apply for this role at Fuse Machines either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.