At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers — intelligently connecting people in more ways, across more devices. We provide app publishers and advertisers with powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs supercharge awareness, acquisition, and monetization. In a rapidly evolving industry, we are constantly innovating and creating better paths of discovery to connect consumers, publishers, and advertisers across the mobile ecosystem. The TeamOur Machine Learning Team plays a pivotal role to deliver on the Company mission. We are a group of research, data science, statistical modeling and machine learning experts driven by passion to solve complex problems and impact we make. We use cutting edge technologies to turn the data into ML solutions deployed across our Products. The Role and Opportunity for YouWe are currently looking for a Machine Learning Engineer to support development of our ML platform that handles TB datasets across over 2B mobile devices to support real time delivery of our ML models. In this role you will have the opportunity to develop your Data Engineering skills towards ML Engineering in low latency environments. You will also benefit from working closely with data scientists and engineers throughout the whole life cycle of ML product development.
Duties and responsibilities
Develop and maintain ETL, or other data pipelines
Develop and maintain inference microservices
Contribute to the design and create ML projects that promote our company objectives
Manage and collaborate on cross-functional technology and data initiatives
Skills and experience
2+ years of experience in data engineering
Bachelor degree in computer science, mathematics, or related field
Proficiency in Java or Scala, experience with Python is an advantage
Knowledge of at least single data processing tool like Apache Beam, Apache Flink or Databricks or Spark
Nice to have: experience with FP Scala - we tend to use CE3 stack in inference
