Software QA Engineer (Machine Learning)

Job Description

Company Description Hyperscience is a market leader in hyperautomation and a provider of enterprise AI infrastructure software. The Hyperscience Hypercell platform unlocks the value of an organization’s back office data through the automation of end-to-end processes, and transforms complex documents into LLM and RAG-ready data to power enterprise GenAI experiences. This enables organizations to transform manual, siloed processes into a strategic advantage, resulting in a faster path to decisions, actions, and revenue; positive and engaging customer, public, and patient experiences; and dramatic increases in productivity. Leading organizations across the globe rely on Hyperscience to drive their hyperautomation initiatives, including American Express, Charles Schwab, Fidelity, HM Revenue and Customs, Mars, Stryker, The United States Social Security Administration, and The United States Veterans Affairs. The company is funded by top tier investors including Bessemer Venture Partners, Battery, FirstMark, Stripes, and Tiger Global. The Team, ML Enablement (MLE) MLE team enables and supports ML teams to conduct experiments, ensure the quality of ML/App integration, and support end-to-end PII redaction and replacement in customer data as well as data deals datasets. Getting Things Done You will have a chance to work with some of the best machine learning, software, and test engineers in one of the most innovative tech companies in Sofia. You will be involved in all stages of the software development lifecycle, from requirements definition and design to development, testing, deployment, and operations. Although your primary focus will be on specific product areas in the ownership of the ML Enablement team, you are expected to consider the overall system quality and user experience. We seek individuals who are eager to contribute their ideas for continuous improvement and who have a strong sense of teamwork, collaborating effectively, and supporting one another. The Role We're looking to grow our Machine Learning team with the addition of a Quality Assurance Engineer. You will be working directly with our world-class Machine Learning engineers and Product team to test and improve our products. As part of the ML Enablement team, and being in MLQA role, you will closely collaborate with application QAs on both, improving the automation framework and testing complex features. You will also have the chance to closely work with some of the best Machine Learning engineers on clearing requirements, and defining testing strategies for in-house ML models but also 3rd party LLMs.

In this role you will:

• Help the teams identify and resolve ML problems
• Create and execute efficient end-to-end manual and automation test cases
• Verify that ML models are integrated properly within the application and are performing as expected
• Report and identify errors and inconsistencies throughout all functional areas
• Extend and execute our load test suite
• Analyze the performance results of ML models
• Extend and execute our model compatibility test suite
• Help with defining and executing testing strategies for LLM/VLM Integrations
• Provide input and status updates regarding test results on a daily basis
• Contribute to the improvement of the automation framework, development and release process
• Work closely with the Product Manager and Engineering Manager to define and clarify requirements
• Identify and research issues with our products
• Work with our Data specialists on anything data-related

Qualifications:

• 2+ years of experience in Software QA with at least 1 year of experience in test automation
• Experience with REST API testing
• Programming skills in any language (but willing to switch to Python)
• Experience working in distributed teams and Agile environment
• Understanding of the Development and Test process and the role of the QA Engineer
• Very good troubleshooting and analytical skills
• Data driven and detail oriented
• Excellent verbal and written communication skills in English
• Self-driven, curious, and highly motivated person willing to learn
• Able to work in collaboration with other team members as well as to meet deadlines
• Willingness to help out in other functional areas and able to adjust to changing priorities
• Trustworthy and energetic team player with a strong work ethic

Nice-to-have:

• Programming skills in Python
• Experience with data analysis, Pytest, CI/CD platforms, Machine Learning
• Experience with Selenium or other Web testing tools and frameworks

Benefits & Perks - You’ll work with some of the best machine learning, software, and test engineers in one of the most innovative tech companies in Sofia - Work from home flexibility - Up to 4 months of fully paid parental leave used within 3 years of your child’s birth - 20 days of paid leave minimum annually with an additional unlimited amount to help nurture work-life symbiosis - A great office, with an excellent location - A sports card, covering various options for sport - Additional health insurance package, including extensive medical, dental & vision care - Truly competitive salary - Stock options - Referral bonus All job applications will be treated and processed with strict confidentiality and in full compliance with the GDPR provisions. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. --- PLEASE BE AWARE of, and cautious about, potential recruitment fraud. All of our open jobs can be found directly on our careers page at: https://www.hyperscience.com/about-us/careers/open-positions/ We will never communicate with candidates except via our @hyperscience.com email domain. Any communication you receive outside of these parameters is potentially fraudulent. Additionally, we never conduct interviews solely via online tests, nor do we make job offers without multiple cross functional live interviews via Zoom, phone or onsite. We only ask for personal information via our application process on our careers page or through a verifiable background check company during onboarding. Apply for this job