Do you believe ensuring that AI models are available and working correctly is even more critical than other software? Are you interested in joining a startup early enough to really innovate while building on a wave of already proven success? Would you like to be part of an AI movement seeking independence from big toy workbenches and cloud roadmap promises?
What You Will Do
As a QA Engineer on our team, you will be creating test cases to validate acceptance criteria for new features, executing them manually or automating them as regression candidates. You will help manage independent test batteries designated for different stages of the development lifecycle, and to leverage configuration management tools to emulate environments for regression of new versions and patches. You will also partner with data scientists to understand the typical business performance metrics and service level objectives commonly established for different types of algorithms, helping to create synthetic data sets to thoroughly test advanced model performance metrics, and to validate our methods for ensuring the quality, reliability, and accurate detection of model degradation.
What Would Help Us
- Insight into how blackbox, smoke, and integration cases combine to provide effective coverage
- Being able to understand and manage your own infrastructure to rule out environmental false positives
- Ability to quickly grasp functional changes and come up with a corresponding set of test cases
- Testing of multi-tenant applications and other SaaS considerations
- Ability to validate test results by gathering data from tables and logs with automation
- Some familiarity with validating data quality, testing ETL processes, and other data engineering
- Of course, experience with ML or testing ML-based applications is great, but not required
What We Offer
- A culture of growth with the room to learn
- Medical/dental/vision insurance plans
- Unlimited PTO
- 100% remote work options
- A talented team around you equally committed to success
- Gym reimbursement
At Datatron, we create technology for the growing number of companies recognizing the need to ensure reliable machine learning as part of their operations, aiding them with the implications of making their proliferating models available and observable. We don't believe only proprietary software or public clouds should make this possible, nor should they dictate what metrics are available to evaluate model effectiveness. We provide customers with their own distributable version of our Kubernetes, Python and React developed platform, and with this, they achieve well-governed model ops, making it easy to catalog, validate, deploy, scale, and continually measure performance for degradation or error...all agnostic to what the model was built with. As the world becomes more reliant on AI to make decisions and draw conclusions, we fill a critical and widening gap today between the models that customers build and train, and the versions that end up fitting their business expectations, while also providing the means to continually assess that they are remaining reliable.
We are an equal opportunity employer and value diversity very highly at our company. For us, diversity is the true key to innovation and everyone in the Datatron family is equally embraced for their unique perspective and experiences. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Datatron is committed to the safety of its colleagues and clients. Given the current status of the COVID-19 pandemic and our current requirement to be in the office physically 3 days a week, we require all employees to show proof of vaccination against the virus. Datatron is committed to following the guidelines set out by the CDC and EEOC. For more information, please see here: https://www.cdc.gov/coronavirus/2019-nCoV/index.html and here: https://www.eeoc.gov/coronavirus.