As an Applied Research AI Engineer, you will help turn the latest advances in AI into practical, scalable solutions for our customers. You will sit at the intersection of research and engineering: investigating new models, evaluation methods, and system designs, then translating them into prototypes and production-ready building blocks.
We are looking for a highly motivated Applied Research AI Engineer to join our AI engineering team. In this role, you will explore state-of-the-art techniques in areas such as LLMs, retrieval systems, agentic workflows, multimodal AI, evaluation, and fine-tuning, and work closely with engineers, project managers, and customers to bring those innovations into real-world use cases.
Key Responsibilities
-
Investigating the latest advancements in generative AI, machine learning, and applied research, and assessing how they can create value for our customers.
-
Designing, implementing, and benchmarking AI systems such as RAG pipelines, copilots, agentic workflows, evaluation frameworks, and fine-tuned models.
-
Translating research ideas, papers, and experiments into robust prototypes and production-ready components.
-
Building reproducible experimentation pipelines for model evaluation, prompt optimization, dataset curation, and system comparison.
-
Collaborating with AI engineers, full-stack developers, and project managers to define technical approaches and integrate research outcomes into customer solutions.
-
Improving model quality, reliability, latency, and cost-efficiency through systematic experimentation and evaluation.
-
Developing and maintaining containerized AI back-ends and research tooling using technologies such as Python, Docker, and FastAPI.
-
Creating clear documentation and technical communication around experiments, findings, trade-offs, and implementation decisions.
-
Contributing to internal best practices around evaluation-driven development, experimentation, and applied AI research.
-
Sharing knowledge with the team through technical mentorship, internal demos, and research reviews.
-
Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related quantitative field.
-
Strong hands-on experience in applied AI, machine learning, NLP, or generative AI, ideally in both experimentation and implementation.
-
Excellent Python skills and experience with modern ML and LLM frameworks such as PyTorch, Hugging Face, LangGraph, LangChain, or similar tooling.
-
Solid understanding of transformer models, embeddings, fine-tuning, prompt engineering, and evaluation methodologies.
-
Experience designing experiments and interpreting results in a rigorous, pragmatic way.
-
Ability to move from research concepts to working prototypes and production-oriented solutions.
-
Strong understanding of software engineering fundamentals, data structures, algorithms, and version-controlled development workflows.
-
Familiarity with cloud platforms and AI services such as Azure.
-
Strong communication skills and the ability to explain complex technical ideas to both technical and non-technical stakeholders.
-
A proactive and curious mindset: you like exploring new ideas, but you also know how to focus on what works in practice.
-
Fluent in English and Dutch. French is a plus.
Nice to Have
-
Publications in relevant AI/ML conferences and journals.
-
Open-source contributions, research repos, or public projects demonstrating strong applied AI work.
-
Experience with LLM evaluation, observability, and benchmarking frameworks.
-
Experience with multimodal systems, synthetic data generation, or post-training methods.
-
Experience deploying AI solutions in enterprise environments.
-
Experience in one of our focus domains: Data Quality, Retail, Manufacturing, Finance.
-
Experience working in consulting, customer-facing delivery, or cross-functional product teams.
We Offer
-
A rewarding salary package that includes additional perks like a company car and fuel card or a mobility budget, comprehensive hospitalization, group insurance, and a top-tier laptop and smartphone.
-
A company culture that stimulates both individual and team development, fostering professional growth.
-
The opportunity to work on meaningful, innovative AI projects that bridge research and real-world impact.
-
Time and space to investigate new tools, frameworks, and methods that can strengthen our technical offering.
-
Regular team-building activities and gatherings, providing great opportunities to unwind and engage with our vibrant team initiatives.
-
A flexible hybrid working policy to choose where, how, and when you want to work.
-
Opportunities to represent Faktion at industry conferences, technical events, and research-driven customer conversations.
