As a Machine Learning Engineer (m/f/d) at Smaato you build the interface between the Data Scientists and Data Engineers, working mostly with TensorFlow, Python and AWS Sagemaker to translate state-of-the-art algorithms from proof-of-concept stage to production-ready solutions.
Due to our cutting edge platform processing an average of 20 billion inbound advertising queries per day, and each of these incoming requests generate multiple outbound requests to our partners, we are talking about more than 12 terabytes of data running on our platform daily.
What You’ll Do:
- Be on the mission to solve complex problems by identifying and optimizing relevant KPIs from a multitude of data
- Develop data pipelines and extract information to predict trends and behavior patterns using data modeling, deep learning, data mining, and machine learning techniques
- Work closely with Data Engineers and Scientists to design statistical and machine learning models
- Deploy machine learning models in containerized applications
- Using Spark, Python / Scala, AWS Services like EMR, ECS, and Kinesis, pulling data from S3 to implement real-time, distributed systems assuring that our machine learning and other data services can easily adapt to our rapid growth
- Own the systems that reliably and performantly serve machine learning predictions in a variety of environments
- Evaluate and test new technologies such as AWS SageMaker
What We’ll Need
- Min. BS in computer science, mathematics, or engineering
- 3+ years of work experience developing and applying machine learning models in production
- 3+ years of work experience developing in Python using the Spark framework
- Vast experience contributing to a large production-grade codebase
- Experience using AWS services and industry knowledge in AdTech are a strong plus
- You know how to monitor and maintain the quality of machine learning pipelines and follow a strict software development flow incl. running tests and writing code reviews
- Full business proficiency in English