Required Staff Algorithm Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Staff Machine Learning Scientist, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Staff Machine Learning Scientist, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more
Our tech stack:
Python, Java, TensorFlow, Spark, Kafka, Cassandra, HDFS, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker.
Requirements: M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
6+ years of hands on experience with coding Deep learning / Machine learning / Reinforcement-learning / Statistical modeling based solutions
4+ years Experience modeling auction dynamics in first-price environments (bid shading, market price modeling, win-rate prediction, clearing-price / floor-price estimation)
Strong knowledge in Python
Good knowledge in Java, Scala or C#
Experience in data analysis and visualization and strong knowledge in SQL
Possess strong problem solving and critical thinking skills
Bonus points if you have:
Deep understanding of RTB ecosystems and standards (OpenRTB), header bidding (Prebid client/server), and ad-exchange integrations
Hands-on experience with budgeting/pacing, frequency capping, throttling, and guardrails to meet margin/CPA/ROAS targets
Strong grasp of measurement and calibration (CTR/CVR calibration, eCPM modeling, lift studies) and experimentation (A/B tests, multi-armed bandits)
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework
This position is open to all candidates.