At AirPR, we are passionate about building software that solves important problems in marketing. We partner with the most valuable companies in the world to transform how they use data and technology to drive marketing and brand decisions. Our software has been used to strategize responses to a brand crisis, discover new content and influencers, and gain an edge in the global online business world.
As a Machine Learning Engineer, you will work on backend algorithms, robust and scalable data ingestion pipelines, machine learning services, and data platforms to support analysis on vast amounts of text and analytics data. You will apply your technical knowledge and Big Data analytics on AirPR’s billions of online content data points to solve challenging marketing problems. Machine Learning Engineers are integral to the success of AirPR.
- Design and build scalable machine learning services and data platforms.
- Create benchmarks and improve models for anomaly detection, seasonality calculations, and event attribution on time series data from multiple sources.
- The system currently processes data on the order of hundreds of thousands of requests per second and terabytes per day.
- Research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes.
- Implement ML, AI and NLP techniques for article analysis and attribution.
- Work with technologies like R, Ruby, Scala, Redis, ElasticSearch, Apache Spark, etc.
- BS, MS, or Ph.D in Computer Science or related field and/or equivalent experience in the space.
- BS, MS, or Ph.D in Statistics or Mathematics or related field and/or equivalent experience in the space.
- Software engineering experience.
- Familiarity with frameworks such as MLlib, scikit-learn, H2O, Torch, TensorFlow, Theano, Caffe.
- Experience with statistical analysis and/or correlation techniques.
- Interest in applying machine learning techniques.