AI Engineer

MCA Nederland; Eindhoven; On-site; EUR 70,000 - 90,000; Full time

Job summary

A leading AI solutions company in Eindhoven, Netherlands, seeks experienced professionals to optimize large language models for edge environments. Responsibilities include enhancing AI system performance and developing agentic capabilities for resource-constrained hardware. Candidates should have postgraduate education, with over 5 years in AI engineering, proficient in Python and C/C++, and a solid foundation in model optimization techniques. This position offers an innovative working environment in a dynamic team.

Qualifications

• 5+ years of experience in software or AI engineering.
• Strong experience with LLMs and performance optimization.
• Experience with model optimization techniques like quantization and pruning.
• Experience with AI deployment toolchains and inference engines.
• Strong programming skills in Python, C/C++, and Linux.

Responsibilities

• Optimize large language models and multimodal models for edge devices.
• Apply optimization techniques to improve model performance.
• Develop agentic AI capabilities and secure workflows.
• Deploy models using various inference engines.
• Translate research into production-ready implementations.

Skills

Experience with large language models (LLMs)

Model optimization techniques

Proficient in Python

Strong programming skills in C/C++

Knowledge of AI frameworks (e.g., TensorFlow, PyTorch)

Familiarity with AI deployment toolchains

Experience with embedded systems

Understanding of safety mechanisms

Strong communication skills

Education

MSc, EngD, or PhD in Computer Science or AI

Tools

PyTorch

TensorFlow

CUDA

TensorRT

ONNX

TFLite

llama.cpp

Job description

In this role, you will help translate advanced AI research into production-ready solutions for edge environments. Your focus will be on optimizing large language models, improving system performance, and developing agentic AI capabilities that can run efficiently on resource-constrained hardware.

Main responsibilities

• Optimize LLMs and multimodal models for deployment on edge and embedded devices.
• Apply model optimization techniques such as quantization, pruning, and distillation to improve performance and efficiency.
• Improve inference performance through system-level optimizations and efficient decoding strategies.
• Develop and implement agentic AI capabilities, including tool orchestration and function calling.
• Design secure and reliable agent workflows, incorporating guardrails and safe tool invocation mechanisms.
• Deploy optimized models using inference engines and frameworks such as llama.cpp, ONNX Runtime, TFLite, and Ollama.
• Build benchmarking pipelines to evaluate the performance of generative and agentic AI systems on-device.
• Develop proofs of concept and demonstrators for edge AI use cases.
• Translate research innovations into production-ready implementations and collaborate with engineering teams to integrate them into products.

What you bring

• MSc, EngD, or PhD in Computer Science, AI, or a related technical field.
• 5+ years of experience in software or AI engineering with strong exposure to LLMs, VLMs, and performance optimization.
• Experience with model optimization techniques such as quantization, pruning, and efficient inference strategies.
• Strong experience with AI frameworks such as PyTorch or TensorFlow.
• Experience with agentic AI frameworks (e.g., LangChain or similar ecosystems).
• Understanding of safety and security mechanisms for AI agents, including guardrails and secure function calling.
• Experience with AI deployment toolchains and inference engines (e.g., CUDA, TensorRT, ONNX, TFLite).
• Experience working with embedded systems, NPUs, or edge AI hardware.
• Strong programming skills in Python, C/C++, and Linux environments.
• Familiarity with MLOps environments, build systems, and cross-compilation workflows is a plus.
• Strong communication skills and experience working in international and cross-functional teams.