Machine Learning Engineer

Responsibilities:

Design data science, statistical, machine learning and deep learning systems that influence millions of players
Implement and optimize appropriate ML algorithms and tools for time series and tabular data
Transform data science prototypes into full-scale products, while deploying and monitoring ML models
Run live tests and experiments
Train and retrain systems when necessary
Create or extend existing ML libraries and frameworks
Collaborate with other scientists, engineers, architects and analysts spread across several countries

Requirements:

MSc in Computer Science, or any related degree
Solid working experience in Python and Java - high coding standards, clean code, well documented, and extensive unit testing- Must.
Experience working with databases (SQL and no-SQL)
Experience with Scala
Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production
Experience with machine learning frameworks (like Keras, Tensorflow, or PyTorch) and libraries (like scikit-learn) - Big Advantage.
Experience with Big Data tools, in particular batch and stream processing (Spark, Kafka, Hadoop, Hive, etc.) - Must
Good understanding of container & orchestration technologies (Docker, Kubernetes, etc.) - Must
Experience working on high-scale, production-grade projects
All-around team player who is a self-motivated, fast learner