QA Data Science Engineer

Reposted Yesterday
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Pune, Mahārāshtra, IND
In-Office
2-5 Annually
Mid level
Information Technology • Security • Cybersecurity
The Role
The QA Data Science Engineer will establish QA best practices for AI-driven security products, perform testing on data pipelines, and integrate ML tests into CI/CD pipelines.
Summary Generated by Built In

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!

Job Description  

We are seeking a Data Science focused QA engineer to develop next-generation Security Analytics products. You will work closely with Data scientists, engineers and product managers to design and optimize AI driven security solutions.  

As QA engineer, the ideal candidate has a strong background in Backend engineering, system integrations, ML,AI and data pipelines. 

Responsibilities (QA Engineer – Data Science / ML) 

  • Establish QA best practices for Traditional ML and Generative AI workflows, including: 

  • Functional and regression testing of ML pipelines using pytest and Airflow/Dagster test utilities and API testing tools (e.g., Postman, pytest-httpx). 

  • Validate data contracts, schemas, and API compatibility across services using Pandera, and custom validation rules. 

  • Model behavior validation (input/output ranges, invariants, edge cases) using NumPy, SciPy, and statistical assertions 

  • Runtime and performance testing for inference latency, throughput, and resource usage using Locust, k6, or custom load tests. 

  • Integrate ML-specific tests into CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins, alongside containerized workflows (Docker, Kubernetes). 
     

  • Implement LLM-specific testing, including: 

  • Prompt and response validation, determinism checks, and regression testing using LangSmith. 

  • Evaluation of hallucinations, toxicity, and policy adherence using LLM-as-a-judge and/or rule-based checks. 

  • Cost, token usage, and timeout monitoring for GenAI workflows 
     

  • Verify logging, monitoring, and alerting for ML services using Prometheus, Grafana, and cloud-native observability tools. 

 

Requirements: 

  • BS or MS in Computer Science or a related field. 

  • 2-5 years of experience in Data or Machine Learning projects. 

  • Familiarity and experience of GenAI applications and tools -PyTorchLangChainvLLM etc. 

  • Demonstrates a commitment to continuous learning in this rapidly evolving field. 

  • Tools listed in the responsibilities section. 

 

Top Skills

AI
Airflow
Backend Engineering
Data Pipelines
Docker
Github Actions
Gitlab Ci
Grafana
Jenkins
K6
Kubernetes
Langsmith
Locust
Ml
Numpy
Pandera
Postman
Prometheus
Pytest
Qa Engineering
Scipy
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The Company
2,736 Employees
Year Founded: 1999

What We Do

Qualys, Inc. (NASDAQ: QLYS) is a pioneer and leading provider of disruptive cloud-based security, compliance and IT solutions with more than 10,000 subscription customers worldwide, including a majority of the Forbes Global 100 and Fortune 100. Qualys helps organizations streamline and automate their security and compliance solutions onto a single platform for greater agility, better business outcomes, and substantial cost savings. The Qualys Cloud Platform leverages a single agent to continuously deliver critical security intelligence while enabling enterprises to automate the full spectrum of vulnerability detection, compliance, and protection for IT systems, workloads and web applications across on premises, endpoints, servers, public and private clouds, containers, and mobile devices. Founded in 1999 as one of the first SaaS security companies, Qualys has strategic partnerships and seamlessly integrates its vulnerability management capabilities into security offerings from cloud service providers, including Amazon Web Services, the Google Cloud Platform and Microsoft Azure, along with a number of leading managed service providers and global consulting organizations. For more information, please visit http://www.qualys.com

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