Datatron is a cutting-edge, MLOps / ModelOps platform for machine learning model deployment, life-cycle management, and governance. Our vision is to give enterprises experience the tremendous benefits of AI by giving them state-of-the-are MLOps toolsets that are typically found in the large cloud players. We are defining the future of model operations and we are just getting started. We are committed to models coming to life in production, and most importantly, stay alive and accurate.
As more and more enterprise companies begin AI programs and leverage Machine Learning to help improve customer experiences and revenue, the opportunity has massive growth potential. Datatron is primed to capitalize on this opportunity. We have built a platform that has already solved major AI/ML pain points for Fortune 100 enterprise brands like Comcast and Domino’s. Datatron helps businesses get more AI/ML models into production faster, delivering business value in less time while providing critical governance for models in production.
Respected industry analysts like Gartner, who have surveyed the competitive landscape, have indicated that Datatron’s product is at the vanguard of the pack. Backed by world-class tier-1 investors. We have proven value, demonstrated by our Fortune 100 clientele. We are in a growth phase and are scaling out teams across the company.
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.
- 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
For more info, please visit www.datatron.com
Datatron is 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