Principal Applied Scientist

About Parloa Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience — one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like IKEA and Booking.com already deploying Parloa at scale. About the role: As a Principal Applied Scientist at Parloa, you will define and drive our applied AI strategy across AI agents and Generative AI. This is a highly hands-on and high-impact role at the intersection of research and production. You will explore, validate, and scale approaches that directly shape our product, from model evaluation and routing to agent behavior, memory, and context engineering, while defining how these systems should be measured, benchmarked, and improved across the industry. Beyond execution, you will act as a technical leader: identifying opportunities, setting direction, and building the foundations of applied science at Parloa. Areas of ownership: Define and lead applied AI initiatives across agent systems, LLM evaluation, and model optimization Own ambiguous problem spaces end-to-end : from framing and experimentation to production impact Design and implement evaluation benchmarking frameworks , leveraging and challenging industry standards—and where needed, defining new ones Drive innovation in agentic systems , including topics like routing, memory, and context engineering Prototype and validate new approaches (e.g., model combinations, fine-tuning strategies, or open-weight models) Translate research into production-ready solutions , working closely with engineering teams Act as a technical authority and multiplier , mentoring others and shaping best practices Establish and lead the Applied Science guild , fostering knowledge sharing and raising the bar across teams Influence product and technical strategy , identifying where applied science can unlock the most value Who you are: 12+ years of experience in Applied Machine Learning, Applied Science, or a related field, with a proven track record of delivering ML/AI systems in production Experience with agent-based systems or multi-step LLM workflows Strong recent experience working with LLMs and Generative AI systems , ideally in production environments Demonstrated ability to own and drive ambiguous problem spaces end-to-end —from problem framing to measurable impact Deep understanding of evaluation methodologies, benchmarking, and model performance analysis , including human-in-the-loop approaches Hands-on technical skills, with the ability to prototype, experiment, and ship solutions in collaboration with engineering teams Experience working on production systems , balancing speed, quality, and scalability Proven technical leadership and influence , with experience shaping direction, mentoring others, or driving cross-team initiatives Ability to operate at both strategic and execution levels , connecting long-term vision with day-to-day decisions Strong communication skills, with the ability to clearly articulate ideas and influence technical and non-technical stakeholders Evidence of broader impact (e.g., published work, open-source contributions, internal initiatives, or industry influence) is a plus We know that great candidates don’t always meet every single requirement. If you’re excited about this role and believe you could make an impact, we encourage you to apply, even if your experience doesn’t perfectly match every qualification. Nice to have Familiarity with model routing, fine-tuning, or open-weight models Background in human-in-the-loop evaluation or annotation systems Contributions to public research, blogs, or open-source projects Our recruiting process: Talent Acqui ... (truncated, view full listing at source)