This is Adyen
Adyen provides payments, data, and financial products in a single solution for customers like Facebook, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
Machine Learning Engineer to join MLOps team
Adyen is seeking a Machine Learning Engineer to join our central MLOps team, which is responsible for building platforms and tools for all of our data science teams. In this role, you will play a crucial part in shaping the MLOps ecosystem at Adyen, serving a variety of machine learning and statistical models for both real-time and batch predictions — from optimizing payments to combating fraud.
What you'll will be doing:
- Own, develop, deploy and operate tooling and services around MLOps:
- Performant model training and tracking.
- Safe, stable and performant machine learning model deployment in both real-time and batch flows, considering latency, reliability and scalability.
- Experiment tracking, validation and hyperparameter optimization runs
- Model monitoring for downtime, latency, and drifts.
- Ensuring scalability of the MLOps infrastructure and bringing MLOps maturity to the next level
- Building tools to democratize machine learning practices at Adyen. Work closely with product machine learning teams to identify their pain-points, way of working.
Who you are
- 4+ years of professional experience as a DevOps Engineer, MLOps Engineer, ML Engineer, Data Engineer
- You have strong software development skills, including: version control (e.g. Git and preferable on Gitlab), coding best practices, debugging, unit and integration testing.
- You have experience with the full machine learning model lifecycle in production flows.
- You have great knowledge of MLOps architectures and practices.
- You are very proficient in python
- You have a very good understanding of software engineering practices
- You have a good understanding of machine learning algorithms, and specifically dependencies on engineering and their lifecycle.
- You have the ability to diagnose and resolve model performance, scalability, and deployment issues.
- You have strong familiarity with the standard data science toolkit, such as (py)spark, MLFlow or similar MLOps frameworks, Airflow
- You have an experimental mindset with a launch fast and iterate mentality.
- Team player with strong communication skills, and are able to convey complex outcomes to a wide range of audiences.
- You are adept at collaborating with cross-functional teams and driving best practices.
Desirable additional qualifications:
- Proficiency with observability tools, such as: Prometheus, Logsearch, Kibana and Grafana.
- Experience in platform engineering and k8s, argoCD, helm is a plus
- Knowledge of kafka or any other streaming framework is a plus
- Knowledge of front end and/or java is a plus
- Experience in working with feature store is a plus
- Experience with setting up and managing GPUs for Accelerated Deep Learning is a bonus
Data positions at Adyen
We know companies handle different definitions for their data-related positions; this is, for instance, dependent on the size of a company. Since the birth of the Data Solution and the growth of all data streams, we categorized and defined all our positions. Have a look at this blogpost to find out!
Our Diversity, Equity and Inclusion commitments
Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you're from, we welcome you to be your true self at Adyen.
Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!
What’s next?
Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.
This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.
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What We Do
By providing end-to-end payments capabilities, data-driven insights, and financial products in a single solution, Adyen helps businesses achieve their ambitions faster.
Our team members are motivated individuals from different cultures that help each other do remarkable things every day and across time zones. We face unique technical challenges at scale and we solve those as a team. And together, we deliver innovative and ethical solutions for businesses all across the world.
With 28 offices across the globe, Adyen serves customers including Meta, Uber, Spotify, Casper, Bonobos and L'Oreal.
Why Work With Us
At Adyen, everything we do is engineered for ambition. We started with payments, at a time when providers offered services based on a patchwork of systems built on outdated infrastructure. Ambition demanded more. So we set off to build a financial technology platform for the modern era, entirely in-house, from the ground up.
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Adyen Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.