Artificial Intelligence / Machine Learning Engineer

Artificial Intelligence / Machine Learning Engineer

Trusted GenAI \& HPC

32–40 hours per week · Hybrid · Eindhoven, the Netherlands

Qualified connects organisations, project ideas and funding opportunities into complete EU project consortia, helping them move from an initial opportunity towards credible projects with lasting European innovation impact. We are building Europe’s digital innovation infrastructure: a scalable business combining structured innovation data, AI\-assisted reasoning and software to find expertise, strengthen collaborations and accelerate EU\-project formation. As AI/ML Engineer, you will build lasting internal artificial intelligence and machine learning (AI/ML) capability that drives the future of our platform.

Your work applies across company initiatives, including GenAISpace, a European project making manufacturing data usable for generative AI while protecting control, confidentiality and intellectual property. You own AI/ML, evaluation, data\-conditioning and high\-performance computing (HPC) decisions; platform/product decisions and incorporation of validated capabilities are shared with Qualified’s team. You will collaborate closely with our small product team and European research, infrastructure and industry partners. Our fine\-tuning, semantic\-reasoning and EuroHPC\-scale capabilities are still being built; you will have the mandate to establish dependable practices, tooling and technical evidence.

What you could achieve in your first year

Depending on priorities, access approvals and partner timelines, your first\-year focus could include:

• Owning our existing Python matching model: establishing an evaluation baseline, then improving it.


• Building governed training and evaluation workflows from local or small\-scale experimentation to approved HPC/AI Factory execution.


• Working with the team to incorporate validated model capabilities reliably into Qualified’s platform.


• Technically validating model capabilities with industrial partners.

• Build and own model capabilities: translate platform/project needs into experiments and delivery; adapt and fine\-tune open\-weight generative models using PyTorch, with parameter\-efficient or full\-training approaches.


• Curate and condition data: define requirements, quality criteria, versioning, provenance, metadata and held\-out evaluation sets.


• Design robust evaluation protocols and baselines for plausibility, factuality, traceability, robustness, bias, hallucinations and failures; ground outputs in approved metadata, dataset passports and pilot evidence.


• Run multi\-GPU/distributed training and inference in HPC/AI Factory environments: resource planning, checkpointing, recovery and performance troubleshooting.


• Establish tracking, versioned configurations, model/data lineage, repeatable evaluation and documentation.


• Implement compute\-to\-data workflows: jobs run where sensitive data is controlled, outputs restricted to approved artefacts, with execution and non\-retention evidence.


• Train and validate manufacturing models with consortium partners. Analyse findings with engineers/domain experts, explain limitations and recommend experiments and deployment.

Essential

• At least four years of relevant professional experience applying AI/ML, preferably in industrial or production\-oriented settings.


• Strong hands\-on applied AI/ML\-engineering experience with production\-quality Python and PyTorch.


• Experience with adaptation or fine\-tuning of transformer\-based or other generative models, including data preparation, training configuration and checkpoint management.


• Demonstrated ability to design meaningful evaluation protocols, analyse model failures and distinguish convincing output from reliable output.


• Solid engineering habits across reproducible workflows: tracking, version control, documented model/data lineage, Git, testing and containerised environments.


• Ability to handle heterogeneous, sensitive or access\-controlled data; translating governance into technical workflow requirements.


• Clear written/spoken English with engineers, researchers and industrial partners.


• An ownership mindset to build capabilities that are not yet mature, while being precise about what has and has not been validated.

• Distributed training/HPC: DeepSpeed, PyTorch FSDP or comparable frameworks; batch/scheduling, profiling and European HPC/AI Factory familiarity. In GenAISpace we will work with the Dutch AI Factory (NLAIF).


• Retrieval/matching: semantic models, ontologies, knowledge graphs, evidence\-linked generation; ranking, recommenders, information retrieval and evaluation.


• Industrial applications: predictive\-maintenance, anomaly\-detection or decision\-support evaluation; collaborative multi\-organisation R\&D.


• Privacy/governed data: privacy\-preserving ML, data spaces, compute\-to\-data, retention and output\-release controls.

What we offer

• Initial contract: One\-year employment contract with the intention to extend.


• Hours: 32–40 hours per week.


• Location and hybrid: Based in Eindhoven, with three office days and up to two home\-working days per week.


• Travel: Occasional travel for GenAISpace, including consortium meetings and the industrial pilot sites in Greece.


• Salary: €4,800–€6,500 gross/month at 40 hours.


• Holiday allowance: 8% of your gross yearly salary.


• Annual leave: 25 days per year at 40 hours.


• Personal development budget: €1,000 per year.


• Travel reimbursement: €0\.23 per kilometre.


• End\-to\-end AI/ML and HPC ownership, building new capability rather than inheriting a fixed stack.


• A key platform\-development role alongside our product team and European partners.


• High autonomy, room for initiative and input that genuinely makes a difference.

1\. A 30\-minute introductory conversation.

2\. A technical deep dive using your own work, portfolio, paper, GitHub project or case, without sharing confidential information.

3\. A final mutual\-fit conversation with the Qualified team.

Our evaluation focuses on your core competencies and how your collaborative approach fits our team culture. We do not use generic coding puzzles or unpaid production assignments.

Qualified aims to complete the process within 10 working days and provide an update within five working days after each step.

Interested?

Send your CV and a short motivation to ted.van.hoof@qualified.technology before September 30th, 2026\. Tell us about an ML system or experiment you owned, how you evaluated it, and what you learned when it did not work as expected.

Job Types: Full\-time, Part\-time

Pay: €4\.800,00 \- €6\.500,00 per month

Work Location: Hybrid remote in 5651 Eindhoven

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