AI/ML Engineer

Huxley Associates
Amsterdam, Netherlands
2 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Amsterdam, Netherlands

Tech stack

API
Artificial Intelligence
Continuous Integration
Information Engineering
DevOps
Python
Machine Learning
Open Source Technology
Peer-To-Peer (P2P)
Systems Integration
Large Language Models
Containerization
Kubernetes
Low Latency
Machine Learning Operations
Docker

Job description

For a client active in retail, we are looking for an AI/ML Engineer to design, build, and deploy cutting-edge machine learning and generative AI solutions, including large language models (LLMs) and agentic systems. You will be responsible for building production-ready pipelines, integrating third-party and open-source models, and creating scalable APIs and tools that leverage state-of-the-art AI. You will support the growth and scalability of a peer-to-peer second-hand marketplace: a second-hand platform for furniture and home goods. This role is part of a newly formed team, offering a real opportunity to deploy machine-learning solutions into production. You will join a cross-functional product team (Product, Engineering, Design) to deploy machine-learning and AI solutions at scale, and you will also be part of the Data & Machine Learning job family, collaborating closely with Data Scientists, Data Engineers, and Data Analysts.

Scope of the consultant services

  • Implement machine-learning models
  • Design, fine-tune, and deploy large language models (LLMs)
  • Integrate with external APIs for large-scale ingestion
  • Build and deploy models to production with high reliability and low latency

Requirements

  • Experienced in monitoring and maintaining model performance, handling retraining and model lifecycle management
  • Experience working with DevOps to scale compute resources cost-effectively across cloud environments
  • Solid understanding of data engineering fundamentals
  • Familiarity with cloud platforms (GCP) and containerization (Docker, Kubernetes)
  • Strong proficiency in Python and modern ML frameworks
  • Solid understanding of MLOps best practices for generative AI (CI/CD, evaluation metrics, prompt testing)
  • Strong problem-solving and analytical thinking
  • Ability to work cross-functionally with product, engineering, and business teams

Most important 3 (as shared)

  • Monitoring & maintaining model performance + retraining & lifecycle management
  • Solid understanding of MLOps best practices for generative AI
  • Strong problem-solving and analytical thinking

Apply for this position