Machine Learning Engineer
About The Position
LSports is a global leader in sports data, committed to revolutionizing the industry with innovative solutions.
Our focus is on sports data collection and analysis, advanced data management, and cutting-edge services such as AI-powered sports tips and high-quality sports visualization. As the sports data landscape grows, we remain at the forefront, delivering real-time solutions.
If you're passionate about both sports and technology and want to drive the sports-tech and data industries into the future, we invite you to join our team.
At LSports, we place a lot of emphasis on Data Integrity, which is a cornerstone of our long-term strategy.
Data Integrity group is at the forefront of real-time analytics, using machine learning and artificial intelligence to balance low latency and impeccable data accuracy.
Responsibilities
- Lead the design and implementation of advanced machine learning algorithms to solve complex problems in various domains.
- Collaborate closely with data scientists and domain experts to operationalize machine learning models into production.
- Mentor junior engineers and provide technical guidance in machine learning best practices.
- Conduct research to keep abreast of the latest advancements in machine learning and artificial intelligence.
- Evaluate the effectiveness of machine learning models through comprehensive validation metrics and make iterative improvements.
**It is possible to work from the offices in Ramat Gan and Ashkelon**
Requirements
- Minimum of 5 years of experience in machine learning or data science, with a proven track record of deploying machine learning models into production.
- Proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of algorithms, data structures, and statistical modeling techniques.
- Advanced degree in Computer Science, Data Science, Statistics, or a related field.
- Demonstrated leadership skills and experience in mentoring or managing teams is an advantage.
Apply
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