Playtika is looking for an experienced technical lead for leading MLE's guild in AI group.
You will join a team of people with exceptional soft skills and outstanding hard skills, that like to share lunchtime together, talking about everyday life, sports, travels, etc. and that transforms into highly trained geeks when extracting leverageable information from Terabytes of structured and unstructured data (per day!).
Playtika MLE development activities are happening in Israel and Switzerland. The MLE tech lead will oversee the entire MLE development life-cycle, MLE tools, infrastructures and technology road map.
- Oversee the overall MLE development life-cycle, from design and planning to implementation and support to maintain a high standard of software quality
- Responsible for work methodologies and tools across all the MLE guild, setting coding and coding review standards, testing standards, interfaces, hand-over procedures with internal customers (like MLOPS), build and release management processes etc.
- Works closely with the DS and infrastructure teams, system architect’s and products spread across several countries.
- Designing and implementing MLE and DS infrastructures.
- Report directly to AI R&D group manager.
- Design data science, statistical, machine learning and deep learning systems that influence millions of players
- Implement and optimize appropriate ML algorithms and tools for time series and tabular data
- Transform data science prototypes into full-scale products, while deploying and monitoring ML models
- Train and retrain systems when necessary.
- Create or extend existing ML libraries and frameworks
- 5+ years’ experience in ML engineering, data engineering
- 2+ years' experience as a tech lead or team leader.
- BSc in Computer Science, or any related degree
- Solid working experience in Python and Java - high coding standards, clean code, well documented, and extensive unit testing
- Experience working with databases (SQL and no-SQL)
- Experience with machine learning frameworks (like Keras, Tensorflow, or PyTorch) and libraries (like scikit-learn)
- Experience with Big Data tools, in particular Batch and stream processing (Spark, Kafka, Hadoop, Hive, etc.)
- Good understanding of container & orchestration technologies (Docker, Kubernetes, etc.)
- Experience working on high-scale, production-grade projects
- All-around team player who is a self-motivated, fast learner
- Strong leadership and organizational abilities.
- Excellent communication, motivational, and interpersonal skills
- Experience with Scala
- Experience with ML platforms (MLflow, Kubeflow, cnvrg.io, etc.)
- 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
- Experience with orchestration/pipelines (Airflow, Ray, etc.)
- Background working with a cloud technology stack
- Experience developing CI/CD workflows and tools (Jenkins, TeamCity, etc.)