Data Scientist AI

Trinamics; Noord-Brabant; On-site; EUR 90,000 - 130,000; Full time

Job summary

Trinamics is seeking an experienced AI/ML engineer to join the Maintenance Assistance team in the Netherlands. You will turn operational challenges into reliable AI solutions, from concept to secure production, working with data scientists and engineers in a multidisciplinary setup.

You’ll design agentic AI apps, multi-agent workflows, and RAG solutions, leveraging Azure OpenAI, LangChain, and MLOps. Fluent English required; Dutch a plus.

Qualifications

• Degree in computer science, artificial intelligence, data science or related field, or equivalent experience.
• Strong Python and PySpark skills with ML/AI libraries.
• Experience with Azure Databricks for ML model development and MLOps.
• Hands-on with generative or agentic AI apps and RAG concepts.
• Familiar with LangGraph, LangChain, and related orchestration tools.
• Experience with Azure OpenAI, embeddings and vector search; English fluency.

Responsibilities

• Design and build agentic AI applications with multi-step reasoning and memory orchestration.
• Develop agentic assistants and multi-agent workflows for operational scenarios.
• Build RAG and knowledge-grounding solutions on structured data and knowledge graphs.
• Develop predictive and decision-support models for maintenance and optimization.
• Analyze data and translate results into actionable insights for domain experts.
• Explore new use cases and asset types, assess data availability and value.
• Build reusable AI services and APIs that integrate with data and cloud services.
• Productize prototypes with CI/CD and observability with security-first mindset.
• Collaborate across Netherlands and India teams on AI/ML initiatives.

Skills

Python

PySpark

APIs

Azure Databricks

MLOps

LangGraph

LangChain

Semantic Kernel

Pydantic AI

AutoGen

Azure OpenAI

Prompting

Vector / Hybrid search

Autonomous workflows

CRISP-DM

English fluency

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

Git

Azure Databricks

API testing

Job description

Trinamics is a well-known, specialized name in technical recruitment in the Netherlands, and a familiar and trusted partner not only for candidates but also for employers. We help technical candidates, from experienced specialists to promising talent, secure a permanent position with strong employers in the high-tech industry. We work on a secondment-to-permanent basis: you start on assignment through Trinamics, with the genuine prospect of a direct contract with the client afterwards. Throughout the assignment, your employment conditions match those of the client’s own workforce, since the client sets these terms itself.

About our client

Our client is an international market leader in automated warehouse and logistics solutions and part of a large global industrial group. Its digital department develops lifecycle capabilities that help customers understand, improve and optimize automated warehouse operations. These include AI-driven operational intelligence, continuous improvement, simulation, emulation and digital twins. Product teams are based in the Netherlands and India and work with Scrum, DevOps principles and short feedback loops.

What you’ll do

You’ll join the Maintenance Assistance team, where data, machine learning and agentic AI come together. You’ll work in a multidisciplinary, international team of AI and data scientists, software and data engineers, domain experts, architects and UX specialists. Together you turn operational challenges into reliable AI solutions and take them from concept and evaluation through to secure, scalable production.

• Design and build agentic AI applications with multi-step reasoning, tool use, memory orchestration and human-in-the-loop controls
• Develop agentic assistants and multi-agent workflows that analyze operational situations, retrieve relevant information and recommend actions
• Build RAG and knowledge-grounding solutions on structured data, documents, events and knowledge graphs
• Develop predictive and decision-support models for maintenance and process optimization, including AI-enhanced process mining, anomaly investigation and root-cause analysis
• Analyze operational and asset data, validate models and translate the results into actionable insights for domain experts, end users and non-technical stakeholders
• Explore new use cases and asset types by assessing data availability and quality, defining approaches and validating value in evolving problem spaces
• Build reusable AI services and APIs that integrate with operational data, digital products and existing cloud services
• Productize prototypes using automated testing, CI/CD and observability, with a security-first approach to privacy, authorization, prompt injection and data leakage
• Collaborate with colleagues in the Netherlands and India, and turn promising developments in generative AI, ML, process mining and event knowledge graphs into practical capabilities

What you bring

• A bachelor’s or master’s degree in computer science, artificial intelligence, data science or a related field, or equivalent work experience
• Strong Python and PySpark skills, including libraries such as pandas, scikit-learn and TensorFlow
• Software engineering experience with API development, automated testing, Git and maintainable application design
• Proven experience with Azure, especially Databricks, for ML model development and MLOps (end-to-end data and ML pipelines)
• Hands-on experience building generative or agentic AI applications, including RAG, agent-based systems and evaluation of AI-generated output
• Experience with orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, Pydantic AI or AutoGen
• Experience with LLM platforms such as Azure OpenAI, and knowledge of prompting, structured outputs, embeddings and vector or hybrid search
• Experience designing autonomous workflows, decision logic and safe tool execution
• Familiarity with the CRISP-DM methodology
• Fluent English; Dutch is a plus
• Nice to have: predictive maintenance, event-driven architecture or Kafka, knowledge graphs, time-series data, Azure AI or Databricks AI services, Kubernetes, AI evaluation and human-oversight design, and industrial warehouse automation