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Machine Learning Engineer
2 years ago
Description
Playtika Holding Corp. is a leading mobile gaming company and monetization platform with over 35 million monthly active users across a portfolio of games titles. Founded in 2010, Playtika was among the first to offer free-to-play social games on social networks and, shortly after, on mobile platforms. Headquartered in Herzliya, Israel, and guided by a mission to entertain the world through infinite ways to play, Playtika has over 3,700 employees in 19 offices worldwide including Tel-Aviv, London, Berlin, Vienna, Helsinki, Montreal, Chicago, Las Vegas, Santa Monica, Laussane, Newport Beach, Sydney, Kiev, Bucharest, Minsk, Dnepr, and Vinnitsa.
Playtika is looking for a Machine Learning (ML) Engineer to join the AI Department.
Playtika provides a one-stop shop for online marketing services to its 15+ online games, making Playtika a major player in the world of Marketing. The marketing AI group enables Playtika’s marketers to optimize decision-making processes by leveraging marketing domain expertise, player data, and top-notch AI.
Responsibilities
- Transform data science prototypes into full-scale products
- Build data science, statistical, machine learning and deep learning pipelines that influence millions of players
- Implement and optimize appropriate ML algorithms and tools
- Train and retrain systems when necessary
- Collaborate with scientists, engineers, architects and analysts spread across several countries
Requirements
- 2+ years experience in software engineering, data engineering or ML engineering
- BSc in Computer Science, Mathematics, or any related degree
- Strong programming skills in Python (at least 2 years of experience)
- Experience working with databases (SQL / no-SQL)
- Experience working on high-scale, production-grade projects
- Familiarity with the following big-data tools: Spark, Kafka, Hadoop, Hive (or similar)
- Experience with Linux OS
- All-around team player who is a self-motivated, fast learner
Advantages:
- Experience with Java and Scala
- Experience with machine learning frameworks (like Keras, Tensorflow, or PyTorch) and libraries (like scikit-learn)
- Familiarity in ML evaluation metrics (Precision, Recall, F1 Score, etc.)
- Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production
- Background working with a cloud technology stack
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