Senior Machine Learning Scientist

Russell Tobin; Amsterdam; Hybrid; EUR 100,000 - 140,000; Full time

Job summary

Russell Tobin is seeking a Senior Machine Learning Scientist to join our MLM Supply Intelligence team in Amsterdam. This hands-on role focuses on building AI and GenAI solutions atop multimodal booking data, including reviews and text.

You will own end-to-end ML/GenAI development, from problem framing to deployment, collaborating with ML Engineers and Product teams to deliver production-ready systems at scale.

Qualifications

• Hands-on experience deploying ML solutions.
• Expert-level Python programming and model development.
• Experience building GenAI applications including RAG pipelines.
• Strong understanding of NLP, Large Language Models, embeddings, retrieval systems, and evaluation methodologies.
• Experience designing experiments and defining meaningful performance metrics.
• Ability to explain technical decisions, trade-offs, and implementation details clearly.

Responsibilities

• Design, build, test, and evaluate Machine Learning and Generative AI solutions end-to-end.
• Develop and optimize GenAI applications, including RAG pipelines.
• Build scalable NLP and LLM-based solutions for business use cases such as review summarization and intelligence generation.
• Define evaluation frameworks, metrics, and experimentation strategies to measure model performance.
• Collaborate closely with ML Engineers and Product teams to deliver production-ready solutions.
• Contribute to and improve existing codebases and AI systems.

Skills

Python

GenAI

NLP

LLMs

Embeddings

Retrieval systems

Model evaluation

Experiment design

Production readiness

Job description

Location: Amsterdam, Netherlands (preferred) | Hybrid (1-2 days/week in office)

About the Role

We are looking for a highly technical and hands-on Senior Machine Learning Scientist to join our MLM Supply Intelligence team. This role focuses on building AI and GenAI solutions on top of large-scale multimodal booking data, including reviews, text, and other customer insights.

You will own the end-to-end development of machine learning and GenAI solutions, from understanding business problems and designing approaches to building, evaluating, and improving models and pipelines. This is an individual contributor role for someone who enjoys coding, experimentation, and solving real-world problems at scale.

Key Responsibilities

• Design, build, test, and evaluate Machine Learning and Generative AI solutions end-to-end.
• Develop and optimize GenAI applications, including RAG (Retrieval-Augmented Generation) pipelines.
• Build scalable NLP and LLM-based solutions for business use cases such as review summarization and intelligence generation.
• Define evaluation frameworks, metrics, and experimentation strategies to measure model performance.
• Select appropriate models and techniques while balancing accuracy, latency, scalability, and cost.
• Translate product and business requirements into practical ML solutions.
• Conduct applied research and rapidly prototype new ideas that can be validated and deployed.
• Collaborate closely with ML Engineers and Product teams to deliver production-ready solutions.
• Contribute to and improve existing codebases and AI systems rather than rebuilding solutions unnecessarily.

Required Skills & Experience

• Strong hands-on experience developing and deploying Machine Learning solutions.
• Expert-level Python programming and model development experience.
• Experience building GenAI applications, including RAG pipelines, prompt engineering, model evaluation, and LLM workflows.
• Strong understanding of NLP, Large Language Models, embeddings, retrieval systems, and evaluation methodologies.
• Experience designing experiments and defining meaningful performance metrics.
• Ability to explain technical decisions, trade-offs, and implementation details clearly.
• Understanding of production considerations such as scalability, latency, infrastructure cost, and performance optimization.
• Proven track record of personally building and delivering ML or AI solutions from concept to implementation.

Nice to Have

• Experience with LLM-as-a-Judge frameworks and advanced evaluation systems.
• Exposure to multimodal AI systems.
• Experience working in fast-paced startup or product-driven environments.
• Strong applied research background with a focus on practical business outcomes.

What We Are Looking For

We are specifically seeking candidates who have personally built ML or GenAI solutions and can explain how their systems work in detail. Candidates whose experience is primarily centered around team leadership, stakeholder management, or high-level architecture without hands-on implementation are unlikely to be a fit.

Successful candidates will demonstrate:

• Strong technical depth rather than buzzword knowledge.
• Ownership of solutions from idea to production.
• Creativity in solving real-world problems.
• A collaborative and humble mindset.
• Strong communication skills and willingness to learn.

You may work on problems such as designing intelligent review summarization systems that process millions of customer reviews, selecting the right models, building evaluation frameworks, and optimizing solutions for scale, quality, latency, and cost.

Ideal Profile

A hands-on Machine Learning Scientist with strong ML fundamentals and practical GenAI expertise who can take a business problem, build an effective solution, rigorously evaluate it, and clearly explain every technical decision behind it.