QA Data Science Engineer

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.

Additional Information

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.

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Company Intel

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