Senior Machine Learning Scientist

Senior Machine Learning Scientist

This is an exciting opportunity to take ownership of high-impact machine learning initiatives within a rapidly growing, AI-driven technology environment. Working at the intersection of machine learning, product development, and marketplace optimization, you will design, build, and deploy intelligent systems that directly influence user engagement, retention, recommendations, and revenue growth. The role offers significant autonomy, allowing you to lead projects from problem definition through production deployment and performance measurement. You will collaborate closely with product managers, engineers, analysts, and AI specialists to transform complex business challenges into scalable machine learning solutions. From recommendation systems and predictive modeling to advanced LLM-powered experiences, your work will shape core product capabilities and deliver measurable impact. This position is ideal for a scientist who combines technical excellence with a strong product mindset and a passion for turning data into meaningful outcomes.

Accountabilities:

• Lead the end-to-end development of machine learning solutions, from problem framing and data exploration through modeling, deployment, monitoring, and optimization.
• Design and implement recommendation systems, ranking models, predictive analytics, retrieval systems, classification models, and AI-powered user experiences.
• Develop and enhance LLM-based applications, including conversational agents, recommendation engines, content generation tools, and intelligent automation systems.
• Build robust evaluation frameworks, monitoring systems, and experimentation processes to ensure model quality, reliability, and business impact.
• Define and track both offline and online performance metrics, connecting model performance to key business outcomes such as retention, engagement, bookings, and revenue.
• Collaborate with engineering teams to deploy scalable production-grade machine learning systems while maintaining performance and latency standards.
• Partner with product, growth, and analytics stakeholders to identify opportunities, evaluate results, and influence strategic roadmap decisions.
• Establish best practices for experimentation, statistical rigor, model evaluation, and machine learning development across the organization.
• Research emerging machine learning techniques and apply practical innovations that improve product performance and user experience.

Requirements:

• 5+ years of experience designing, building, and deploying machine learning models in production environments.
• Strong proficiency in Python, SQL, and modern software development practices for machine learning applications.
• Proven experience delivering end-to-end machine learning projects that generated measurable business impact.
• Deep expertise in at least one key area such as recommendation systems, search and ranking, natural language processing, embeddings, predictive modeling, causal inference, or LLM-based systems.
• Hands-on experience with modern AI technologies including prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation frameworks, and agent-based architectures.
• Strong understanding of experimentation methodologies, statistical analysis, A/B testing, and model performance evaluation.
• Experience collaborating closely with product and engineering teams in fast-paced, product-driven environments.
• Ability to balance cutting-edge innovation with practical, scalable business solutions.
• Excellent communication and documentation skills, with the ability to clearly explain technical concepts to diverse audiences.
• Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, Data Science, or a related field preferred; PhD or research experience is highly valued.

Benefits:

• Competitive salary package complemented by early-stage equity participation.
• Fully remote working environment with flexibility across European time zones, including the United Kingdom.
• High levels of ownership and autonomy over technical direction and project execution.
• Opportunity to work on cutting-edge machine learning, recommendation systems, and generative AI technologies.
• Collaborative and AI-native engineering culture that embraces modern development tools and rapid experimentation.
• Direct influence on product strategy and business outcomes through data-driven innovation.
• Flexible, asynchronous work environment that supports work-life balance.
• Professional growth opportunities within a rapidly scaling technology company.
• Exposure to challenging, real-world marketplace and consumer behavior problems at scale.
• Inclusive, collaborative culture that values curiosity, initiative, diversity of thought, and continuous improvement.