Senior Machine Learning Engineer at Pennylane · Paris

Are 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!

Our vision

We 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.

About us

Pennylane is one of the fastest growing Fintechs in France (and soon in Europe!). In 5 years of existence, we've managed to:

• 💻 Make ourselves known as a groundbreaking accounting and financial software for small businesses and their accountants
• 💰 Raise 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
• 👨‍👩‍👧‍👦 Grow 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
• 🌍 Build 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
• 🤝 Earn the trust of thousands of customers and accounting firms, with outstanding ratings
• 🚀 Reach more than 1,000,000 small and medium-sized enterprises (SMEs) and over 6,000 accounting firms using Pennylane in France

WHY this position is of utmost importance to reach our mission

At Pennylane, every decision that is not backed by data is likely to be challenged (when data is available of course). This culture is embraced by the leadership team, and actively promoted everywhere. The role of the data team is to make this possible by treating data like a production asset, making it available company-wide, and using it proactively to improve Pennylane’s user experience.

By joining us as a Senior Machine Learning Engineer, you will have a pivotal role in large projects, bringing your engineering and machine learning expertise to help us meet our high delivery standards.

HOW you will contribute to the company as a Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will be part of the Machine Learning team (10+ people), inside the Data department (50+ people).

• You will design machine learning solutions and tools across the entire ML lifecycle, from model training and tuning to deployment, inference, experimentation and monitoring.
• You will contribute to all parts of our Data Platform, from data ingestion and validation to transport, storage and exposure to consumers, in order to feed machine learning applications in production.
• You will work closely with fellow Machine Learning Engineers and Data Engineers to improve our ecosystem and enable a variety of ML applications.
• You will collaborate with Product teams to explore new possibilities and make sure that fulfilling user needs is always at the center of what we do.

WHAT you can expect from your life at Pennylane

Within one month:

• You will learn everything about our company, our teams, and our vision during the first onboarding week.
• You will get familiar with our stack, and have delivered a few small projects which will give you a concrete taste of our tools & processes.
• You will be given time to meet your future stakeholders, and gain a deep knowledge of our product and operations.

Within 3 months:

• You will be fully in charge of items in our roadmap, defining and prioritizing your tasks autonomously.
• You will be confortable with our technical stack (Python, PySpark, Redshift, Airflow, AWS Sagemaker).
• You will contribute to larger cross-team projects.

Within 6 months:

• You will proactively contribute to the team’s roadmap.
• You will work with engineers and data practitioners on improving our stack and data platform.
• You will share your learnings and best practices within the team.

And beyond: the data team will continue growing with the company

Which means:

• Opportunities to recruit and mentor new team members,
• Increased accountability in project leadership,
• Responsibilities to design and implement new processes, tools and best practices to make sure that your team works even more efficiently.

What does the recruitment process look like?

• A first interview with our Talent Acquisition Manager
• A case study interview to discuss a topic closely related to one of our priorities (75 min)
• A past project interview to hear about your experience (60 min)
• An interview with our Tech & Product leaders to discuss our company culture

🇫🇷 Données personnelles

Pennylane 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 : dpo@pennylane.com. Notre data policy

🇬🇧 Personal Data

Pennylane 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 dpo@pennylane.com. Learn more

🇩🇪 Personenbezogene Daten

Pennylane 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 dpo@pennylane.com schreiben. Mehr erfahren