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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in training and fine-tuning deep learning models, with a strong command of Python and ML frameworks such as PyTorch or JAX. Proficient in managing the full model lifecycle, from data curation to production deployment, while collaborating effectively with engineering teams.
Highest-signal resume keywords
Deep Learning Model TrainingPython ProgrammingML Frameworks (PyTorch, JAX)Model Lifecycle ManagementHugging Face Ecosystem
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Deep LearningModel Fine-TuningData PipelinesExperiment TrackingModel EvaluationModel DeploymentScaling ModelsModern Model ArchitecturesData CurationPerformance Metrics
Soft Skills
Autonomous Decision-MakingProblem-Solving
Tools & Technologies
Hugging Face TransformersHugging Face DatasetsHugging Face Hub
Industry Keywords
Computer ScienceElectrical EngineeringMathematicsPhysics
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Research, design, and train models suited to the specific needs of our products
- Fine-tune existing open-source and foundation models to maximize accuracy and performance
- Own the full model lifecycle: data curation, experimentation, evaluation, and production deployment
- Collaborate with mobile and backend engineers to integrate models directly into our apps
- Define and track the metrics that drive quality — and continuously push them in the right direction
Requirements
What you’ll need- A degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related technical field
- Hands-on experience training or fine-tuning deep learning models that are used in production
- Strong Python skills and experience with ML frameworks (PyTorch or JAX preferred)
- Comfort with the full model development cycle: data pipelines, experiment tracking, evaluation, deployment, and scaling
- Solid understanding of modern model architectures and when to apply them
- Experience with the Hugging Face ecosystem (Transformers, Datasets, Hub) is a strong plus
- Ability to work autonomously, make decisions under uncertainty, and ship without waiting for perfect conditions
Benefits
Comp & perks- Attractive compensation, above market average
- Hybrid work model based in Barcelona
- High ownership from day one — you define the direction, not just execute on it
- Work directly with the founders and a senior, low-ego team
- A real product with real users — your work will have immediate, measurable impact