Machine Learning Engineer - MLOps
Top vacature
04-10-2024
Marktconform
Medior
Amsterdam
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
