Machine Learning Engineer Data & Engineering · TBAuctions | Amsterdam ·

TBAuctions; Amsterdam; On-site; EUR 80,000 - 95,000; Full time

Benefits offered by this job

Pension scheme

Bonus scheme

Laptop and iPhone

25 vacation days

Training opportunities

Modern data stack (FastAPI, Databricks

Job summary

TBAuctions in Amsterdam seeks a Machine Learning Engineer to build and deploy ML models, AI agents, and production systems. You will translate data science work into scalable services, collaborate with software engineers, and implement real-time AI solutions using modern tooling.

You should have 7+ years of industry experience, a Master in CS or related field, and hands-on expertise with Python, PySpark, ML libraries, and model serving in Kubernetes environments.

Qualifications

• 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.

Responsibilities

• Develop and implement machine learning models to address business challenges.
• Deploy machine learning models into production systems for real-time applications via API as scalable microservices.
• Build, serve, deploy, evaluate and monitor production-grade AI agents.

Skills

Python

PySpark

MLlib

Scikit-learn

TensorFlow

PyTorch

MLflow

Kubernetes

AKS

API deployment

Education

Master's in Computer Science

Data Science / Mathematics background

Tools

Databricks

FastAPI

Job 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.

What you will do

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.

What you bring

• 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

Bonus Points

• 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.

What we offer you

• Independent and varied role within an entrepreneurial and innovative organization

• Modern data stack (FastAPI, Databricks, Airflow, DBT, PowerBI)

• Yearly salary of € 80.000 - € 95.000 (including holiday allowance), depending on experience

• Good pension scheme

• Bonus scheme (up to 1 gross monthly salary per year)

• 25 vacation days

• Laptop and iPhone

• Training opportunities

• Working in a team of professionals, where hard work is well combined with humor