AI Engineer

ASAP Staffing Ltd; Amsterdam; Hybrid; EUR 75,000 - 110,000; Full time

Benefits offered by this job

Hybrid working model

Exposure to real production-scale AI

Job summary

ASAP Staffing Ltd. is seeking AI Engineers across the full spectrum of AI/ML work in the Netherlands. Roles include model development, deployment, and production infrastructure for real-world applications, with emphasis on ML/DL modelling, LLMs, NLP, computer vision, and MLOps.

You may work on data pipelines, RAG-enabled apps, and production-ready AI systems while collaborating with product, data, and engineering teams. Open to juniors through senior levels, with hybrid flexibility.

Qualifications

• Open from strong juniors (1–2 yrs) to senior/lead (10+ yrs).
• Please specify your seniority and area of specialization in your application.

Responsibilities

• Design, train, and evaluate ML/DL models for real product use cases.
• Build and deploy LLM-powered applications (RAG, agents, fine-tuning, prompt engineering).
• Create data pipelines and infrastructure to support ML systems at scale.
• Take models from research to production (optimization, latency, reliability).
• Apply MLOps practices: CI/CD, containerization, monitoring, versioning.
• Collaborate with product, data, and engineering teams to translate business needs into AI solutions.
• Evaluate models, run experiments, and improve performance based on data.

Skills

Python

SQL

Java

C++

R

PyTorch

TensorFlow

Scikit-learn

HuggingFace Transformers

LangChain

Pandas

NumPy

Tools

Databricks

Spark

FAISS

Pinecone

Milvus

pgvector

Job description

About Us

We're building AI-driven products and systems, and are growing our AI engineering team in the Netherlands. We're casting a wide net across the AI/ML/Data ecosystem from applied ML engineers to LLM/GenAI specialists to MLOps and AI infrastructure experts because we want to understand the full range of talent and experience available in the market before we finalize our hiring plan.

Whatever your specialization within AI, we'd like to hear from you.

The Role

We're looking for AI Engineers across the full spectrum of AI/ML work, including (but not limited to):

• Machine learning & deep learning model development
• Generative AI, LLMs, RAG, and multi-agent systems
• NLP, computer vision, and predictive modelling
• MLOps, model deployment, and production infrastructure
• AI research applied to real-world/production systems

What You Might Work On

• Designing, training, and evaluating ML/DL models for real product use cases
• Building and deploying LLM-powered applications (RAG, agents, fine-tuning, prompt engineering)
• Building data pipelines and infrastructure to support ML systems at scale
• Taking models from research/prototype to production (optimization, latency, reliability)
• Applying MLOps practices CI/CD, containerization, monitoring, versioning
• Collaborating with product, data, and engineering teams to translate business needs into AI solutions
• Evaluating models, running experiments, and improving performance based on data

Who We Want to Hear From

We welcome applications from a wide range of backgrounds, including:

• AI/ML Engineers model development, deployment, and production ML
• Data Engineers with ML exposure pipelines, ETL/ELT, data infrastructure
• AI Researchers with applied/production experience
• Computer Vision / NLP specialists
• Technical AI educators / course developers (if you also train or mentor others)
• Candidates from adjacent fields (software engineering, data science) with strong AI/ML exposure

Experience level: Open from strong juniors (1–2 yrs) through senior/lead (10+ yrs). Please specify your seniority and area of specialization in your application or cover note.

Core Skills We're Interested In (any subset)

Programming: Python, SQL, Java, C++, R

Frameworks: PyTorch, TensorFlow, Scikit-learn, HuggingFace Transformers, LangChain/LangGraph, Pandas, NumPy

Data & Infra: ETL/ELT, Data Pipelines, Databricks, Spark, Data Warehousing, Vector Databases (FAISS, Pinecone, Milvus, pgvector).

Other valued experience: Model evaluation/observability (Ragas, Langfuse), red-teaming, A/B experimentation, technical writing, stakeholder communication.

What We Offer

• Competitive, experience-based compensation (open to discussing your expectations).
• Hybrid working model with flexibility.
• Exposure to real, production-scale AI systems not just research.
• Collaborative team environment across a range of AI specializations.
• Growth path based on demonstrated impact, regardless of formal title coming in.