Model AI Engineer
Indexed description
You will bridge the gap between raw data and production-ready intelligence.
🌞Day-to-day life
Operational & Tactical Management
- Train and fine-tune models independently using state-of-the-art frameworks.
- Design rigorous experiment plans, including benchmarking and ablation studies, to drive model evolution and improvement.
- Design dataset preparation, filtering, and versioning strategies and tools to ensure high-quality training data.
- Define evaluation protocols, apply model optimisation techniques, and export models for specific production targets.
- Maintain reproducible experiment pipelines and produce detailed technical evaluation reports.
- Workflow Improvement by proposing and implementing enhancements to internal training and evaluation workflows.
- Contribute to the definition of model engineering standards and review experiment pipelines developed by junior team members.
- Coordinate with Production Engineers on model I/O and constraints, and support external technical demos or presentations.
Ability to identify bottlenecks and propose technical solutions.
Skilled at translating complex model behaviors into clear reports and collaborating across teams.
A continuous learning mindset and receptiveness to peer feedback.
Experience
3-6 years of experience in AI Model Engineering
Degree in Computer Science, Data Science, Mathematics, or a related field.
Deep understanding of the AI model lifecycle, MLOps fundamentals, and model optimization.
Proficiency in both English and Spanish is required.
🎸 You will rock it if
You feel identified with this technical knowledge:
- AI & Model Engineering
- Frameworks: Advanced Python, PyTorch, and TensorFlow (specifically custom loops).
- Libraries: HuggingFace (Transformers/Datasets), OpenCV, Albumentations.
- MLOps & Tools: MLflow (experiment tracking), DVC (versioning), and Optuna/Ray Tune (hyperparameter tuning).
- Optimisation: Model quantisation, pruning, and ONNX validation.
- Data Analysis: Proficiency in pandas profiling, data drift checks, and bias analysis (distribution skew, label bias).
- Environment: Docker, Bash scripting, and SQL (advanced queries).
- CI/CD: GitFlow, GitLab CI, or GitHub Actions.
- Cloud: Basic experience with AWS S3 or similar cloud storage.
- Testing: Advanced usage of pytest and config-driven pipelines.
- Multimedia: Basic knowledge of GStreamer development is a plus.
- Salary range: 30k-40k gross salary
- Wellness support: An extra €55 gross per month to spend on wellness sessions or activities. 🧘♂️
- Remote work allowance: An extra €30 gross per month to help cover your home office expenses.
- Private medical insurance included: Fully covered by Cigna ⚕️. Plus, special rates if you want to add your family members.
- Flexible remuneration: Optimize your salary with ticket transport, restaurant, and kindergarten vouchers via Cobee. 🍕
- Continuous learning & development: We heavily invest in your personal and professional growth in different ways: 📚
- A personal training budget of €400 per year.
- Language training.
- 2 days off per year to attend workshops and/or conferences.
- Flexibility & work-life balance: 💗
- Core hours: From 10:00 h to 16:00 h (Monday to Thursday), and 10:00 h to 14:00 h on Fridays. The rest of your working day is flexible! 👥
- 30 days of remote work per year from a different location than your usual one. 🌍
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