- Location
- Antwerp, Vlaams Gewest, Belgium
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Machine Learning
- Seniority
- Senior
- Education
- Master
- Source
- Recruitee
Description
As a Junior AI Engineer at Faktion, you'll jump-start your career working on a wide variety of hands-on projects across industries like manufacturing, finance, and operations. You won't just build prototypes—you will do real engineering, ship models to production, and build systems that deliver real-world impact. As a junior member of our team, you will be paired with experienced senior engineers and technical leads who will mentor, guide, and support your professional growth as you scale up your technical skill set.
Key Responsibilities
End-to-End AI Engineering: Design and implement end-to-end AI solutions spanning GenAI, classical ML, computer vision, and agentic systems tailored to enterprise customers, working alongside senior architects.
Architecture & Scoping: Work with senior engineers and product managers to translate client problems into concrete technical architectures and clear technical requirements.
Production Backends: Develop and deploy production-ready AI backends using Python, FastAPI, and Docker, focusing on scalability, code quality, and system reliability.
Evaluation Pipelines: Build and maintain continuous evaluation frameworks (including LLM-as-a-Judge agents) to track model quality from development to production.
MLOps & Pipeline Maintenance: Build and maintain reliable MLOps workflows covering data preprocessing, feature extraction, model training, and performance monitoring.
Continuous Learning & Research: Research emerging advancements in Generative AI, machine learning, computer vision, and deep learning, identifying practical applications for client projects.
Cross-Functional Collaboration: Collaborate closely with software engineers, designers, and business stakeholders to ensure technical implementations match customer goals.
Technical Documentation: Author clear technical documentation, architectural notes, and presentations to explain complex AI concepts to both technical and non-technical stakeholders.
Mentorship & Professional Growth: Actively participate in structured 1-on-1 mentorship, code reviews, and pair programming sessions with senior team members to continually elevate your engineering practices.