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October 7

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Resilinc

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Enterprise • AI • SaaS

Resilinc is a leading provider of supply chain risk management and resiliency solutions. The company uses advanced technologies such as AI for mapping, monitoring, and predictive analytics to offer deep supply chain visibility and risk scoring. With their proprietary data, Resilinc helps businesses ensure continuity by forecasting disruptions and collaborating effectively with global suppliers. They serve industries including aerospace, healthcare, and high-tech manufacturing, providing tools for compliance, business continuity planning, and ESG adherence. Their services cater to various business roles including CEO, CPO, and supply chain resiliency managers.

201 - 500 employees

Founded 2010

🏢 Enterprise

☁️ SaaS

📋 Description

• Develop and implement QA strategies for AI-powered applications, focusing on accuracy, bias, fairness, robustness, and performance. • Design and execute automated and manual test cases to validate AI Agents/LLM models, APIs, and data pipelines and good understanding of data integrity, data models, etc. • Assess AI models using quality metrics such as precision/recall and hallucination detection. • Test AI models for bias, fairness, explainability (XAI), drift, and adversarial robustness. • Validate prompt engineering, fine-tuning techniques, and model-generated responses for accuracy and ethical AI considerations. • Service/tool development. • Conduct scalability, latency, and performance testing for AI-driven applications. • Collaborate with data engineers to validate data pipelines, feature engineering processes, and model outputs. • Design, develop, and maintain automation scripts using Selenium and Playwright for API and web testing. • Work closely with cross-functional teams to integrate automation best practices into the development lifecycle. • Identify, document, and track bugs while conducting detailed regression testing to ensure product quality.

🎯 Requirements

• Proven expertise in testing AI models, LLMs, and Generative AI applications, with hands-on experience in AI evaluation metrics and testing tools like Arize, MAIHEM, and LangTest. • Strong proficiency in Python for writing test scripts and automating model validation, along with a deep understanding of AI bias detection, adversarial testing, model explainability (XAI), and AI robustness. • Demonstrate strong SQL expertise for validating data integrity and backend processes, particularly in PostgreSQL and MySQL. • Strong analytical and problem-solving skills with keen attention to detail, along with excellent communication and documentation abilities to convey complex testing processes and results.

🏖️ Benefits

• Full-stack benefits for health, wealth and wellbeing