Senior ML Engineer, Embedded AI — Remote EU

Pennylane; Madrid; Presencial; EUR 80 000 - 110 000; Tempo integral

Resumo da oferta

Pennylane is seeking a Machine Learning Engineer — Embedded AI to design and ship ML systems for document understanding and classification. You will own the full lifecycle from problem framing to deployment, improve production ML practices and collaborate with product and engineering teams to integrate AI into our accounting workflows.

You should have 5–8 years of experience, be strong in Python, and capable of building scalable ML systems in production.

Qualificações

• Have 5–8 years of experience building and operating ML systems in production.
• Strong Python expertise and software engineering mindset.
• Ability to frame problems, establish baselines and select meaningful metrics.
• Experience in document AI, NLP, classification, ranking or recommendations.
• Fluent in English; French not mandatory.

Responsabilidades

• Design and ship ML systems for document understanding, extraction and classification.
• Own full lifecycle: framing, data strategy, baselines, training, deployment, monitoring.
• Improve production systems through data collection, error analysis and feedback loops.
• Contribute to Copilot and Autopilot experiences with measurable value.
• Collaborate with Product, Engineering and domain experts to integrate ML into the user experience.

Conhecimentos

Python

Production ML systems

Problem framing & metrics

Document AI

English fluency

Ferramentas

PyTorch

PySpark

Redshift

Airflow

AWS SageMaker

Descrição da oferta de emprego

Pennylane is seeking a Machine Learning Engineer — Embedded AI to design and ship ML systems for document understanding and classification. You will own the full lifecycle from problem framing to deployment, improve production ML practices and collaborate with product and engineering teams to integrate AI into our accounting workflows.

You should have 5–8 years of experience, be strong in Python, and capable of building scalable ML systems in production.