> Markdown version of [/jobs/ext/3610991-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3610991-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** TBAuctions - **Location:** Amsterdam, Netherlands - **Experience:** Expert - **Salary:** €6,667.0 - €7,917.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Python (Programming Language), Machine Learning, Recommender Systems, Tensorflow, Software Engineering, Data Processing, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Prompt Engineering, Model Validation, Agentic-AI, Fastapi, Kotlin, Event Driven Architecture, Spark Mllib, Containerization, Pyspark, Scikit Learn, Kubernetes, Information Technology, Performance Monitor, Azure AKS, Machine Learning Operations, Virtual Agents, Programming Languages, Microservices - **Published:** October 8, 2026 - **Apply:** https://www.adzuna.nl/details/5917846952 ## About the Role * 7+ years of industry experience * Master's in Computer Science, Statistics, Mathematics, or related field * Proven experience in developing and deploying machine learning models in production environments * Knowledge of API deployment and model serving, including containerization and orchestration with Kubernetes and Azure Kubernetes Service (AKS) * Proven organizational and project management skills * Expert in programming languages such as Python and Pyspark * Strong understanding of data manipulation, statistical analysis, and machine learning algorithms (MLlib, Scikit-learn, TensorFlow/Pytorch, MLflow) * Experience building AI agents and components such as memory, context engineering, retrieval, and orchestration, including multimodal retrieval systems/architecture. * Excellent communication skills and ability to work in a collaborative team environment * Familiarity with event-driven architecture and hands-on experience with serving ML models as microservices * Experienced with recommender systems at scale * Experienced in working on high-load, real-time AI solution * Experience with a programming language such as Java or Kotlin. ## Description At TBAuctions, we are committed to building intelligent auctioning platform for our brands. We are seeking a Machine Learning Engineer to join our team with a primary focus on building machine learning models, AI agents, and deploying them into production environments. The ideal candidate will have a strong background in data science, machine learning, AI engineering, and software engineering to effectively translate models into scalable solutions. Machine Learning Model Development: * Develop and implement machine learning models to address business challenges. * Conduct data analysis, feature engineering, and model selection to optimize performance. Model Productionization: * Deploy machine learning models into production systems for real-time applications. * Serve models via API deployment as scalable microservices, containerized and orchestrated with Kubernetes and Azure Kubernetes Service (AKS). * Collaborate with software engineers to integrate models into existing infrastructure. AI Agent Deployment: * Build, serve, deploy, evaluate and monitor production-grade AI agents. (LangGraph, RAG, MLFlow and FastAPI). Performance Monitoring, Evaluation and Optimization: * Monitor model performance in production, investigate drift, and iterate to improve evaluation metrics. * Conduct A/B testing and validation to assess model impact and reliability. Cross-functional Collaboration: * Work closely with cross-functional teams to understand business requirements and translate them into technical solutions. * Communicate complex technical concepts to non-technical stakeholders effectively. Documentation and Reporting: * Create reproducible, versioned documentation of modeling development, experiments, and results. * Produce reports and presentations that communicate methods, findings, and recommendations.