Senior Machine Learning Scientist, Engineer

November 20

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Laivly

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Artificial Intelligence • SaaS • Enterprise

Laivly is a company that provides collaborative AI solutions for contact centers, empowering customer service agents through automation and support tools. Their key product, a cobot named Sidd, integrates seamlessly with existing technology stacks to enhance efficiency, accuracy, and customer satisfaction. Laivly's solutions offer real-time transcription, call summaries, and AI-driven support across multiple communication channels, such as email, chat, SMS, and social media, without requiring replatforming. The company focuses on ethical AI use, ensuring their technology respects user rights and privacy while providing measurable improvements in contact center performance.

51 - 200 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

📋 Description

• Lead prompt design, optimization, versioning, and documentation • Generate and maintain synthetic datasets for pre-release validation and testing • Design and run experiments to measure accuracy, robustness, and safety of LLM behavior • Define and monitor key metrics such as hallucination rates, latency, token cost, and regression risk • Build evaluation pipelines, dashboards, and drift detection tools • Implement rigorous statistical methods and produce reproducible reports with effect sizes and confidence intervals • Investigate regressions or prompt failures in production and coordinate mitigation with stakeholders • Collaborate with cross-functional teams on model integration, rate limiting, and cost controls • Maintain prompt libraries, test suites, and operational runbooks

🎯 Requirements

• Bachelor’s degree in Computer Science, Computational Linguistics, Statistics, or related field; Master’s preferred • 2+ years working directly with LLMs, prompt design, or applied NLP in production • Experience creating synthetic datasets using programmatic generation or controlled sampling • Deep knowledge of experimental design, statistical inference, and power analysis • Strong Python programming skills and familiarity with statistical/ML frameworks • Experience defining observability for model outputs and instrumenting alerting systems • Familiarity with cloud environments (AWS, Azure), Kubernetes, and production deployment practices • Proficiency in SQL and experience with reproducible analysis pipelines

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities