QA Data Science Engineer
qualys · Pune ·
- Category
- Data science
- Experience
- 2+ years
qualys · Pune ·
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 -PyTorch, LangChain, vLLM etc.
Demonstrates a commitment to continuous learning in this rapidly evolving field.
Tools listed in the responsibilities section.