Staff Machine Learning Engineer

Curious about what it's like to work at the world's number 1 discovery platform as a Staff Machine Learning Engineer? We're glad you asked!

Taboola, the world's largest content recommendation platform, is hiring a Staff Machine Learning Engineer.

At Taboola, we currently work in a hybrid work model giving employees the flexibility to work from home a few days a week. We have offices in Ramat Gan and Beer Sheva and are looking to grow to additional locations such as Jerusalem, where our Taboolars have the opportunity to meet their teammates, connect with other teams and socialize with friends.

What are some of the things you do on a day-to-day basis?

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 company's revenue
Work on a daily basis with some of the hottest trends in today's 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
Provide technical leadership and mentor team members on best practices, code reviews, data-insights, analysis results and machine learning technical designs.
Own end-to-end projects involving multiple stakeholders, from architectural design and data pipeline configuration to production deployment and performance optimization.
Be a key contributor to product and engineering roadmaps, influencing decisions that affect millions of users daily.
You will report directly to the group manager.

Our tech stack:

Python, Java, TensorFlow, Spark, Kafka, Cassandra, HDFS, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker

What are the skills a good Machine Learning Engineer needs to have?

Required:

M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
Strong knowledge in Python
Good knowledge in Java, Scala or C#
8+ years of hands on experience with coding data-science / machine learning / statistical modeling based solutions
3+ years of hands on experience in Recommendation Systems, Real Time Bidding or e-Commerce.
Familiarity with deep learning / classic machine learning / reinforcement learning / multi-armed bandits algorithms.
Experience in data analysis and visualization and strong knowledge in SQL
Possess strong problem solving and critical thinking skills

Preferred:

Experience in leadership, mentorship and cross-team collaboration.
Experience to effectively communicate complex technical solutions and influence business stakeholders
Experience developing deep learning algorithms in a large-scale, real-time production environment.

Why Taboola?

Taboola is the world's leading recommendation platform reaching over 500 million daily active users. We're growing rapidly, and have recently gone public on the NASDAQ.
Adam Singolda, Taboola Founder and CEO says; "You can copy anything from another business but you can't copy a company's culture."
If you ask our employees what they love about Taboola they will tell you that here, they are able to discover their best professional selves, explore where they can grow to, and learn from and together with smart and talented people.
At Taboola, we pride ourselves in making an impact on how people consume content across the world, a culture of transparency, passion, and a diverse, inclusive and friendly work environment.
You can get to know us more by visiting our company website, careers site, Taboola Life blog and social media channels; Facebook, Instagram, Twitter and LinkedIn

Sounds good, how do I apply?

It's easy, submit your CV by clicking the "Apply" button below.

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