Machine Learning Engineer

• A state-of-the-art agentic LLM pipeline that crafts answers and executes e-commerce actions, bringing value to both Gorgias and our customers at scale.
• Relies on multiple providers, including in-house fine-tuned models.
• Uses A/B testing to validate prompt engineering.
• Includes a retrieval-augmented generation (RAG) system that contextualizes customer requests using ANN, rerankers, feedback loops, and knowledge graphs.
• Classical NLP classification algorithms that identify non-support-related emails, detect intent, and infer customer sentiment.
• Clustering based on minimum-cost flow problems to discover new knowledge resources from non-automated interactions.
• A product recommendation system that drives sales and conversions on merchant websites.

What you’ll do

As part of the Machine Learning team, you will play a crucial role in developing, refining, and scaling our AI Agent, which automatically addresses and resolves shopper requests for our merchants. You will optimize and implement solutions that enhance the efficiency, accuracy, and functionality of our AI-driven customer support and marketing solutions.

• Machine learning:
• Own feedback loops, observability, and continuous training for deployed systems and models (Hugging Face, Vertex AI, multiple LLM providers)
• Work on agentic LLM systems, retrieval-augmented generation (RAG), and NLP classifiers.
• Solve product-facing problems using classical NLP and/or LLMs.
• Keep up with the latest advances in mathematics and computer science.
• Maintain the ML team’s data pipeline (BigQuery, dbt)
• Engineering:
• Write clear technical specifications and implement scalable solutions using domain-driven design, enabling fast, reliable, and safe iterations.
• Maintain our existing services.
• Own the development lifecycle.
• Collaborate in a cross-functional team to provide machine learning as a service within Gorgias.
• Collaborate with data engineers, software engineers, and product managers to understand requirements and incorporate feedback.
• Analyze post-release performance and identify improvements for next iterations.

• Experience: 5+ years of experience and a proven track record in machine learning and software development, with hands-on experience building and operating LLM applications, RAG systems, agentic workflows, and NLP classifiers.
• Technical skills: Proficiency in Python, modern machine learning and software engineering tools and frameworks. Familiarity with GCP is a plus.
• Communication: Excellent written and verbal communication skills in English, with the ability to articulate complex concepts to both technical and non-technical stakeholders.
• Education: Master’s degree in a STEM field (science, technology, engineering, or mathematics) or a related field.

• Competitive salary & equity (90th percentile worldwide, go check our public salary calculator)
• 5-week vacation plus 2 weeks RTT (We follow each country’s appropriate PTO Laws)
• Paid sick leave
• Paid parental leave (16 weeks)
• MacBook Pro
• Personal credit card to buy lunches (we use Swile)
• We provide private health insurance (we use GAN)
• Get up to €700 to set up your workstation at home (working from home should feel breezy)
• Get up to €2000 of learning material and wellness support per year! This includes €1500 for learning material (such as books, courses, and individual coaching sessions) directly linked to your job scope, as well as a €500 wellness budget. Take advantage of these resources to grow in your role and prioritize your personal development and wellness.
• Every quarter, we organize an online company-wide summit to discuss where we’re going and strengthen social bonds. Once per year we organize offsite team retreats and company retreats!

AI at Gorgias At Gorgias, AI is a natural extension of how we work and build. Our teams use it every day to research, write, analyze, code, and craft better customer experiences. Everyone has access to premium AI tools (ChatGPT, Claude, Granola & others) and an annual L&D budget to explore new ones.

The real magic happens when we share what we learn. Our #powerup Slack channel is a digital petri dish of new tools and workflows, and each team has AI champions who showcase fresh ideas during weekly company-wide standups, now practically AI demo sessions.

We see AI not as a replacement for creativity or empathy, but as a multiplier, helping us move faster, think deeper, and serve customers better.

At Gorgias, we’re building the platform that makes this real: a unified AI agent that sells, supports, and re-engages customers across the entire journey. Conversational Commerce is the future of ecommerce, and we’re leading that shift.

Our mission is to turn every interaction between a brand and its customers into a relationship: personal, seamless, and intelligent. By combining deep product expertise with the latest in AI, we’re making shopping feel more natural, human, and connected than ever before.

To win, we focus relentlessly on:

• Quality: conversations that feel authentic and on-brand.
• Experience: effortless shopping from chat to checkout.
• Re-engagement: personal, 1-1 dialogue instead of noisy marketing.

The opportunity is massive. As AI reshapes how people buy, Gorgias is building the foundation for the next decade of ecommerce, where every brand has its own intelligent agent and every customer feels understood.

Join us to make Conversational Commerce real.

About the Machine Learning Team

Join our Machine Learning team, where we’re transforming the ecommerce landscape by automating interactions between merchants and shoppers. Our mission is to make these experiences effortless for everyone involved.

Our team includes Software Engineers, Machine Learning Engineers, Product Managers, and Designers who work together to advance AI-driven customer support. Our main focus is building an AI Agent that can accurately and efficiently respond to customer inquiries and drive sales!

As a company:

• We serve 15K+ e-commerce businesses.
• We handle 1M+ merchant-shopper interactions per day.
• We recently raised a $30 million Series C (Crunchbase article).