ppAre you looking to have an impact on the daily life of millions of entrepreneurs in France (and tomorrow in Europe)?
Are you looking for a work environment that values trust, proactivity, and autonomy?
Are our Engineering principles aligned with your vision?
Then Pennylane is the right place for you!
/p h3Our vision /h3 pWe aim to become the most beloved financial Operating System of French SMEs and Accounting Firms (and soon, European ones).
We help entrepreneurs rid themselves of time-consuming tasks related to accounting and finance while giving them access to the key financial information they need to make the best decisions for their business.
/p h3About Us /h3 ul liMake ourselves known as a groundbreaking accounting and financial software for small businesses and their accountants /li liRaise a total of €400 million, including from Sequoia — the famous Silicon Valley fund that invested early in companies like Google, Facebook, Airbnb, Stripe and Paypal /li liGrow from 7 cofounders to 1,000 happy Pennylaners, and earn a place among the greatest companies to work for in France (and remotely), with a 4.6/5 rating on Glassdoor /li liBuild an international environment with more than 25 nationalities and a strong remote-friendly culture, where 30% of employees already work from all parts of Europe /li liEarn the trust of thousands of customers and accounting firms, with outstanding ratings /li liReach more than 1,000,000 small and medium?sized enterprises (SMEs) and over 6,000 accounting firms using Pennylane in France /li /ul h3WHY this position is of utmost importance to reach our mission /h3 pPennylane is becoming the financial OS of European SMEs and accounting firms.
A growing share of the work done inside our product will be automated or assisted by AI.
Our strategy operates at three layers: verticalized AI embedded in the product, an agent interface that makes Pennylane readable and actionable by AIs, and the Pennylane orchestrator agent itself.
The bEmbedded AI /b team owns the first layer.
We build the specialized machine learning systems behind Copilot and Autopilot: invoice parsing, document classification, accounting suggestions, matching, scoring, Bookkeeping Autopilot and Revision Autopilot.
Models are commoditizing fast.
What makes the difference is our ability to frame the right problem, use Pennylane's data and accounting knowledge, evaluate quality on real workflows, and operate reliable systems in production.
By joining us as a Machine Learning Engineer — Embedded AI, you will turn difficult accounting problems into trusted ML products used every day.
You will combine strong ML engineering, product thinking and production ownership to improve both automation and user trust.
/p h3HOW you will contribute as a Machine Learning Engineer — Embedded AI /h3 ul liYou will design and ship ML systems for document understanding, extraction, classification, matching, ranking, scoring and recommendations.
/li liYou will contribute directly to our Copilot and Autopilot experiences, including Bookkeeping Autopilot and Revision Autopilot.
/li liYou will own the full lifecycle of your solutions: problem framing, data and labeling strategy, baselines, training,



evaluation, deployment, experimentation, monitoring and maintenance.
/li liYou will turn user corrections and production failures into better datasets, models and product behavior.
/li liYou will define quality metrics that reflect real user value: precision and recall, automation coverage, straight-through processing, human correction rate, latency and cost.
/li liYou will partner with Product, Engineering and accounting experts to understand workflows, define what "correct" means and integrate ML naturally into the user experience.
/li liYou will choose the simplest reliable approach for each problem — deterministic logic, classical ML, deep learning or generative AI — rather than starting from a preferred model.
/li liYou will help improve our shared ML engineering practices: reusable components, experimentation, observability, data quality and reliable training and inference pipelines.
/li liYou will stay ahead of the curve by monitoring emerging ML and AI techniques — including multimodal and generative models — and applying them when they create measurable value.
/li /ul h3WHAT You Can Expect From Your Life At Pennylane /h3 h3Within one month: /h3 ul liYou will learn about Pennylane, our users, our accounting workflows and our AI vision during onboarding.
/li liYou will get familiar with our ML stack, production systems, datasets, metrics and ways of working.
/li liYou will meet your product and engineering partners and contribute to a first scoped improvement.
/li /ul h3Within 3 months: /h3 ul liYou will own an Embedded AI use case end to end, with clear offline and production metrics.
/li liYou will have shipped a meaningful improvement to a Copilot or Autopilot capability.
/li liYou will be comfortable with our technical stack, including Python, Pytorch, PySpark, Redshift, Airflow, AWS SageMaker and our monitoring tools.
/li liYou will use real user feedback and error analysis to prioritize the next iterations.
/li /ul h3Within 6 months: /h3 ul liYou will lead larger cross?team ML projects and help shape the Embedded AI roadmap.
/li liYou will improve the reliability, automation coverage and maintainability of one or more production systems.
/li liYou will share best practices and raise the bar for ML engineering, evaluation and production ownership across the team.
/li /ul pAnd beyond: the ML AI teams will continue growing with the company /p h3Who are we looking for?
/h3 ul liHave 5–8 years of experience and are very strong in Python.
/li liHave hands?on experience building and operating machine learning systems at scale in production — not only training models or running notebooks.
/li liKnow how to frame an ambiguous product problem, establish a baseline and select useful metrics before optimizing a model.




/li liHave strong experience in several of these areas: document AI, NLP, classification, ranking, recommendation, anomaly detection, deep learning or generative AI.
/li liCare about data quality, observability, failure modes, cost and long?term maintainability as much as model performance.
/li liHave a balanced blend of technical, business and product skills, and communicate well with software engineers, product managers and non?technical domain experts.
/li liAre fluent in English; French is not mandatory.
/li /ul h3Nice to have: /h3 ul liExperience with accounting, fintech or other high?trust business workflows.
/li liExperience with human?in?the?loop systems, active learning or learning from user corrections.
/li liExperience running ML systems at scale with strict latency, reliability or cost constraints.
/li liFamiliarity with multimodal or generative models for document understanding.
/li /ul h3What does the recruitment process look like?
/h3 ul liA first interview with our Talent Acquisition Manager /li liA case study interview covering problem framing, data, modeling, evaluation, deployment and monitoring (75 min) /li liA past project interview to discuss your experience and technical decisions (60 min) /li liAn interview with our Tech Product leaders to discuss our company culture (30 min) /li /ul h3Données personnelles /h3 pPennylane traite vos données pour gérer votre candidature et évaluer votre adéquation au poste.
Si votre candidature n'aboutit pas, vos données peuvent être conservées 2 ans à compter de notre dernier échange ou de la clôture du recrutement afin de constituer gérer un vivier de candidats.
Vous pouvez vous opposer à tout moment et demander la suppression de vos données en écrivant à : /p pNotre data policy /p h3Personal Data /h3 pPennylane processes your data to manage your application and assess your suitability for the position.
If your application is unsuccessful, your data may be retained for 2 years from our last exchange or the closing of the recruitment process, in order to build and manage a candidate pool.
You may object at any time and request the deletion of your data by writing to Learn more /p h3Personenbezogene Daten /h3 pPennylane verarbeitet Ihre Daten, um Ihre Bewerbung zu bearbeiten und Ihre Eignung für die Stelle zu beurteilen.
Sollte Ihre Bewerbung nicht erfolgreich sein, können Ihre Daten bis zu 2 Jahre ab unserem letzten Austausch oder dem Abschluss des Rekrutierungsverfahrens gespeichert werden, um einen Kandidatenpool aufzubauen und zu verwalten.
Sie können jederzeit Widerspruch einlegen und die Löschung Ihrer Daten beantragen, indem Sie an schreiben.
Mehr erfahren /p h3Datos personales /h3 pPennylane trata sus datos para gestionar su candidatura y evaluar su idoneidad para el puesto.
En caso de que su candidatura no sea seleccionada, sus datos podrán conservarse hasta 2 años a partir de nuestro último contacto o de la finalización del proceso de selección, con el fin de constituir y gestionar una reserva de candidatos.
Puede oponerse en cualquier momento y solicitar la eliminación de sus datos escribiendo a /p pMás información /p /p #J-*****-Ljbffr

📌 Senior Machine Learning Engineer - Embedded Ai (Lazio)
🏢 Pennylane
📍 Lazio