Acceldata is reimagining the way companies observe their Data!
Acceldata is the pioneer and leader in data observability, revolutionizing how enterprises manage and observe data by offering comprehensive insights into various key aspects of data, data pipelines and data infrastructure across various environments. Our platform empowers data teams to manage products effectively by ensuring data quality, preventing failures, and controlling costs.
As a SDET [ML]
You will be responsible for ensuring the quality and reliability of machine learning models and related software systems. You will work closely with ML Engineers to develop and execute automated testing frameworks, design test strategies, and validate the performance and robustness of ML systems.
A day in the life of SDET [ML]
Constructing test scenarios based on User Stories or requirements for AI/ML applications.
Developing and maintaining systematic test cases for AI/ML applications.
Develop unit, integration, and end-to-end tests to ensure the correctness and performance of ML systems.
Build and maintain a suite of tests for model training, validation, inference, and deployment.
Work with machine learning engineers to validate model behaviour, output accuracy, and performance.
Identify and troubleshoot issues related to data quality, model drift, bias, and performance degradation.
Ensure that ML models meet business requirements and comply with quality standards.
You are a great fit for this role if you have
- Bachelor's degree in Computer Science or a related field.
- 2-4 years of experience in software testing.
- Strong programming skills in Python and other scripting languages.
- Experience in designing and executing tests for ML/LLM performance, accuracy, and relevance.
- Hands-on experience with building processes, CI/CD processes, and managing QA environments.
- Experience working with build management tools like Git and Jenkins.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
- Ability to work independently as well as in a team environment.
We care for our team
· Mentorship & Growth
· ESOPs
· Medical and Life Insurance
· Paid Maternity & Parental Leave
· Corporate Uber Program
· Learning & Development Support
Acceldata for All
We are a fast-growing company, solving complex data problems at scale. We are driven by strong work ethics, high standards of excellence, and a spirit of collaboration. We promote innovation, commitment, and accountability. Our goal is to cultivate a healthy work environment that fosters a sense of belonging, encourages teamwork, and brings out the best in every individual.
Why Acceldata?
Acceldata is redefining data observability for enterprise data systems. Founded by experts who recognized the need for innovative monitoring and management solutions in a cloud-first, AI-driven environment, our platform empowers data teams to effectively manage data products. We address common challenges such as scaling and performance issues, cost overruns, and data quality problems by providing operational visibility, proactive alerts, and monitoring reliability across the various environments.
Delivered as a SaaS product, Acceldata's solutions have been embraced by global customers, such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Zoominfo, GSK, Oracle, PubMatic, PhonePe (Walmart), Hersheys, Dun & Bradstreet, and many more. Acceldata is a Series-C funded company and its investors include Insight Partners, March Capital, Lightspeed, Sorenson Ventures, Industry Ventures, and Emergent Ventures.
Top Skills
What We Do
Founded in 2018, Campbell, CA-based Acceldata has developed the world's first enterprise data observability platform to help enterprises build and operate great data products.
Acceldata's solutions have been embraced by global customers, such as Dun & Bradstreet, Verisk, Oracle, PubMatic, PhonePe (Walmart), and many more.
Acceldata investors include Insight Partners, March Capital, Industry Ventures, Lightspeed, Sorenson Ventures, Sanabil, and Emergent Ventures. Contact us to learn about the benefits of data observability.