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 Acquisition → Technical Peer Interview → 360° Technical Interview Loop → Bar Raiser

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Role

As a Senior Research Scientist focused on Robotic Foundation Models, you will be responsible for the design and implementation of systems that enable the training, deployment, and utilization of large-scale AI models for robotics. You will guide technical direction, mentor engineers, and ensure the development of robust, scalable ML models  required to make robots significantly more capable in real-world environments. Your work will empower both internal teams and external partners by providing accessible tools and infrastructure for injecting advanced machine learning techniques into robotic applications.

How your work moves the mission forward

• Lead the design and implementation of infrastructure and architecture of large-scale robotic foundation models.
• Oversee the training and deployment of robust ML models for high-performance robotic applications.
• Empower ML researchers and engineers with accessible tools and infrastructure for developing and applying AI techniques in robotics.
• Collaborate with product and engineering teams to define infrastructure requirements and deliver successful solutions for partners and customers.

Skills you will need to be successful

• PhD in Computer Science / Engineering with a specialization in Machine Learning and / or Robotics.
• Experience collaborating on medium to large software projects for at least 4 years.
• Experience in programming Python / C++ and machine learning frameworks (Tensorflow, JAX).
• Demonstrable experience with offline Reinforcement / Imitation Learning in a robotics context.
• Proven ability to work with a team, setting directions and driving towards solutions.

Skills that will differentiate your candidacy

• Academic track record of publications in the field of offline Reinforcement / Imitation Learning in Robotics.
• Experience with Robotic Foundation Models / Vision-Language-Action Models.
• Experience with Online Reinforcement Learning and / or Computer Vision for Robotics.
• Experience with deploying ML services at scale, e.g., via cloud computing and containerization (Google Cloud, Docker, Kubernetes), databases (SQL, no-SQL), and service-oriented architecture frameworks.