Sr. Software Engineer - Machine Learning Revenue

Sr. Software Engineer – Machine Learning Revenue

5+ years of experience in machine learning, with a proven track record of building models to deliver impactful solutions at scale.
PhD or MS in machine learning, computer science, statistics, or another highly quantitative field.
Experience with one or more of the following – causal inference, reinforcement learning, uplift modeling, contextual bandits, conversion rate prediction.
Hands-on experience in designing and building large-scale ML systems.
Hands-on experience in using big data batch/stream processing frameworks such as Spark and Flink.
Proficiency in deep learning frameworks such as PyTorch, Tensorflow, etc. as well as general purpose ML frameworks such scikit-learn and SparkML.
Proficiency in Python, Scala, Java or similar programming languages.

Apply state-of-the-art machine learning techniques, including causal inference, reinforcement learning, deep learning and optimization in the monetization domain.
Leverage your expertise to optimize our promotions strategy and recommend most relevant premium products to our users.
Design and implement cutting-edge machine learning algorithms using deep learning frameworks and distributed data processing frameworks such as Spark.
Work with big data (handling 1.6B+ user swipes per day) to improve the accuracy and relevance of our prediction models.
Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives.

Hands-on experience applying machine learning in the monetization domain
In-depth knowledge and understanding of deep neural networks.
Demonstrable experience in designing and implementing large-scale ML systems with low latency serving
A strong record of publications in top conferences such as NeurIPS, ICML, and KDD
A deep understanding of the scientific theory behind machine learning techniques.