Senior Machine Learning Engineer

Beeswax’s mission is to build great advertising software. Our product is an easy to use, massive scale and high availability advertising platform founded by industry veterans who worked together at Google. We offer our customers the most extensible and transparent advertising system in the world and process billions of transactions per second. We’ve been acquired by Comcast’s FreeWheel. Joining our team means an even bigger vision than before, as well as increased benefits and access to resources for you to make an impact. 

We are looking for a Senior Machine Learning Engineer with an in-depth working knowledge of the latest in Machine Learning/Data Science technologies and cloud platforms to join our Optimization team. 

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In this role you’ll work on a wide range of computational challenges such as: CTR prediction, forecasting, incrementality, bidding models, and delivery optimization. We practice an effective data science process that recognizes the uncertainty in explorations for ML solutions but also emphasizes an agile software engineering workflow. We use the most popular tools in the Python data science ecosystem and embrace innovation. 

Our tech stack is always evolving to meet the challenges of the massive scale of transactions on which we operate. To manage the firehose of data coming in, we explore complex tradeoffs and carefully architect high performance distributed systems. Those in turn require elegant and thoughtfully designed interfaces to make the systems accessible to both our team and our customers. 

Responsibilities 

• Lead and execute data science projects and ensure they deliver business value 
• Work with the product and engineering team to build data model pipelines to power customer-driven products 
• Implement and test the latest research works and advise strategic directions 

Required Qualifications 

• MSc or above in a STEM (science, technology, engineering, mathematics) subject 
• Solid knowledge on machine learning 
• 5+ years of demonstrable experience with machine learning engineering in industry 
• Expert-level proficiency in Python and SQL, and ML ecosystem in Python 
• Good understanding of engineering best practices, agile and version control 
• Effective collaboration and communication with cross function teams 

Desired Qualifications 

• Practical experience with data warehousing, especially Snowflake 
• Practical experience with cloud platforms, especially AWS 
• Practical experience in distributed computing frameworks, especially Apache Spark and distributed Tensorflow  
• Excellent academic or industrial track record