QA Engineer - AI/ML
AccessHope ● Remote
At AccessHope, we’re Fighting cancer with everything we know™ by putting the ever-growing body of cancer knowledge to work for the greater good. Through a revolutionary employer health benefit offering, we remotely connect employees with cancer support services from National Cancer Institute (NCI)–Designated Comprehensive Cancer Centers. Instead of requiring those who have been diagnosed with cancer to come to the centers for renowned cancer expertise, AccessHope brings their support to the patient and their local oncologist—wherever they’re located—to improve care, outcomes, and value.
Hopeful for those we support, rebellious in our approach, and collaborative by breaking down barriers, AccessHope is seeking a Quality Assurance Engineer to help us uniquely deploy the latest cancer knowledge to the places it’s needed most. As an ideal candidate, you’ll be an integral part of our team ensuring the quality and reliability of our AI/ML-driven applications. Your role will involve designing and executing comprehensive test strategies, validating machine learning models, and collaborating closely with cross-functional teams to deliver cutting-edge, robust solutions.
Key Responsibilities
- Evaluate and validate machine learning models for accuracy, reliability, and performance.
- Develop and execute test plans for various AI/ML components, including algorithms, models, and data pipelines.
- Ensure the quality and integrity of training and validation datasets used for machine learning models.
- Collaborate with data scientists to understand data requirements and verify the correctness of data transformations.
- Verify the functionality of AI algorithms, assessing their behavior across different scenarios and edge cases.
- Perform white-box and black-box testing of AI algorithms to uncover potential vulnerabilities and biases.
- Collaborate with software developers to integrate AI/ML components into larger software systems.
- Conduct end-to-end testing to validate the seamless integration of AI/ML features.
- Identify and address bottlenecks and performance issues related to AI/ML components.
Required Qualifications
- Bachelor’s degree in computer science, Software Engineering, or a related field. 4 years of experience plus min experience may substitute for minimum education requirements.
- 5+ years of Proven experience in testing AI/ML models and understanding of machine learning concepts.
Preferred Qualifications
- Master’s degree in computer science, Software Engineering, or a related field.
- Familiarity with tools and frameworks used in AI/ML
- Proficiency in programming languages such as Python, with an emphasis on scripting for testing purposes.
- Strong analytical and problem-solving skills, particularly in the context of AI/ML applications.
- Experience with data validation, feature engineering, and understanding of data preprocessing for machine learning.
Additional Information
- Virtual within the Continental U.S.; support or collaboration across multiple time zones; may include travel up to 25%
- As a condition of employment, AccessHope requires staff to comply with all state and federal vaccination mandates.
- The estimated pay scale represents the typical pay range AccessHope reasonably expects to pay for this position, with offers determined based on several factors which may include, but not be limited to, the candidate’s experience, expertise, skills, education, job scope, training, internal equity, geography/market, etc. This pay scale applies to the current posting only.
AccessHope is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, identity, age, status as a protected veteran, or status as a qualified individual with disability.