Senior MLOps Engineer

Realize your potential by joining the leading performance-driven advertising company!  

As a Senior MLOps Engineer on the Infra group, you’ll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.

About Algo platform:

The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.

The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership. 

The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence. 

To thrive in this role, you'll need:

• Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
• Highly skilled in software engineering methods. 5+ years experience. 
• Passion for ML engineering and for creating and improving platforms 
• Experience with designing and supporting ML pipelines and models in production environment
• Excellent coding skills - in Java & Python
• Experience with TensorFlow - a big plus
• Possess strong problem solving and critical thinking skills
• BSc in Computer Science or related field.
• Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
• Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
• Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.

Bonus points if you have:

• Experience in leading Algorithms projects or teams.
• Experience in developing models using deep learning techniques and tools
• Experience in developing software within a distributed computation framework

How you’ll make an impact:

As a Senior MLOps Engineer Engineer, you’ll bring value by:

• Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more 
• Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
• Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
• Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
• Build and maintain tools for automation, deployment, monitoring, and operations.
• Troubleshoot issues in our development, production and test environments
• Influence directly on the way billions of people discover the internet

Our tech stack:

Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins

If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:

• Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.
• Well-being: Enjoy comprehensive benefits (health, etc.), a fully stocked kitchen, and location-specific perks (gym partnerships, parking).
• Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired.
• Work with some of the biggest names: We work with some of the biggest names in the business. Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, Expedia and Honda.

Ready to realize your potential?

Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.-

Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog.

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.

Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.

By submitting your application/CV, any personal information you provide will be subject to Taboola’s Candidates Data Policy. Please review our policy carefully before submitting any of your personal information. You may contact us at [email protected] with any questions about how we collect or use your personal information, or your applicable rights.

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