Senior Machine Learning Engineer – Embedded AI

Posted Sep 9

This is a fully remote position, open to applicants in France.

πŸ“‹ Description

β€’ Design and deploy machine learning systems focused on document comprehension, extraction, classification, matching, ranking, scoring, and recommendations.

β€’ Contribute to the Copilot and Autopilot experiences, which include Bookkeeping Autopilot and Revision Autopilot.

β€’ Manage the entire lifecycle of solutions, encompassing problem identification, data and labeling strategies, baseline establishment, training, evaluation, deployment, experimentation, monitoring, and maintenance.

β€’ Transform user corrections and production failures into enhanced datasets, models, and product functionalities.

β€’ Establish quality metrics such as precision, recall, automation coverage, straight-through processing, human correction rates, latency, and cost.

β€’ Collaborate with Product, Engineering, and accounting specialists to comprehend workflows and incorporate machine learning into the user experience.

β€’ Choose dependable methods, including deterministic logic, classical machine learning, deep learning, or generative AI.

β€’ Enhance shared machine learning engineering practices, create reusable components, and improve experimentation, observability, data quality, and training/inference pipelines.

β€’ Keep track of emerging machine learning and AI techniques, including multimodal and generative models.

β€’ Oversee an Embedded AI use case from start to finish and implement enhancements to Copilot or Autopilot.

β€’ Lead extensive cross-team machine learning projects and contribute to shaping the Embedded AI roadmap.

β€’ Enhance the reliability, automation coverage, and maintainability of production systems.

β€’ Share best practices throughout the ML & AI team.


⛳️ Requirements

β€’ 5–8 years of professional experience.

β€’ Proficient in Python with strong programming skills.

β€’ Practical experience in building and managing machine learning systems at scale in a production environment.

β€’ Ability to define ambiguous product challenges, set baselines, and identify useful metrics.

β€’ Strong expertise in areas such as document AI, NLP, classification, ranking, recommendation, anomaly detection, deep learning, or generative AI.

β€’ Commitment to data quality, observability, failure modes, cost-effectiveness, and long-term maintainability.

β€’ Well-rounded technical, business, and product management skills.

β€’ Ability to communicate effectively with software engineers, product managers, and non-technical domain experts.

β€’ Proficient in English; knowledge of French is a plus.

β€’ Full work authorization in France, Spain, Portugal, Germany, Italy, the UK, Ireland, Greece, Poland, Romania, or Croatia.

β€’ No visa sponsorship is available.

β€’ Experience in accounting, fintech, or other high-trust business workflows is a plus.

β€’ Familiarity with human-in-the-loop systems, active learning, or learning from user corrections is advantageous.

β€’ Experience in running machine learning systems at scale with strict constraints on latency, reliability, or cost is a plus.

β€’ Knowledge of multimodal or generative models for document understanding is an added advantage.


🏝️ Benefits

β€’ Remote-friendly culture.

β€’ Opportunity to work remotely from eligible European countries.

β€’ Opportunities to mentor new team members.

β€’ Opportunities to lead significant product initiatives.

β€’ Chance to help define technical standards.

β€’ Comprehensive onboarding and access to the ML stack, production systems, datasets, metrics, and working methodologies.

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