Machine Learning Engineer

Job details

Work model

Not provided by source

Salary

Not listed by source

Location

Amsterdam

Occupation

Computer Systems Engineers/Architects(O*NET 15-1299.08)

Hiring context

How this role compares at Adyen

Adyen has 228 live roles in MeritLog’s catalog across 10 job families, and 70 of them are in data & analytics. 65 of those listings publish a pay range, a disclosure rate of 29%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

This is Adyen At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of Adyen are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help businesses achieve their ambitions faster. 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 (I, II and Senior) Adyen is looking for a Machine Learning Engineers (II and Senior) to join our team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. You will be responsible for designing, productionizing and maintaining machine learning services that power data products at Adyen. Teams Currently Hiring: • Customer Risk • Account Risk Engine • Behavioural Fraud In this role, you will: • Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment. Examples ML domains are: on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling; • Identify and fix performance bottlenecks in ML training and inference (memory consumption, online latency, training time etc.); • Collaborate with software engineers to integrate ML solutions into products and services; • Collaborate with data scientists to transition research prototypes into scalable solutions; • Collaborate with MLOps and platform teams to integrate effectively with current tools, and shape priority for future tools; • Support and encourage good engineering practices on product ML teams; Who You Are: • You have 5+ years of experience as an engineer working in the machine learning domain; • You are a strong Python programmer; • You have experience with the full machine learning model lifecycle in production flows; • You have experience leveraging big data to create the pipelines needed to feed the models with appropriate data; • You have a strong understanding of good software engineering practices as well as data engineering and MLOps principles; • You have knowledge of data science, statistics and machine learning techniques; • You have strong familiarity with the standard data science toolkit in python, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow; • You have knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana • You have an experimental mindset with a launch fast and iterate mentality; • You proactively take the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences. Nice to Have: • You have experience with distributed GPU compute environments • You have experience working with a Machine Learning ‘Feature Store’ 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 is a full-time position based in our Amsterdam office, and it requires relocation if you are currently living outside of the Netherlands.