Zefr

About Zefr

Contextual targeting for smarter video advertising

🏢 Tech👥 251-1K📅 Founded 2009📍 Venice, California, United States

Key Highlights

  • Headquartered in Venice, California
  • Over $100 million raised in funding
  • Specializes in contextual targeting for YouTube
  • Serves major brands in entertainment and consumer goods

Zefr is a video advertising technology company headquartered in Venice, California, specializing in contextual targeting solutions for brands on platforms like YouTube. With a focus on enhancing brand safety and audience engagement, Zefr serves a diverse clientele, including major brands in the ente...

🎁 Benefits

Zefr offers competitive salaries, equity options, flexible PTO, and a remote work policy that supports a healthy work-life balance....

🌟 Culture

Zefr fosters a culture of innovation and collaboration, encouraging employees to explore new ideas in the rapidly evolving video advertising landscape...

Zefr

Mlops Engineer Lead

ZefrMarina Del Rey - On-Site

Posted 3w ago🏛️ On-SiteLeadMlops Engineer📍 Marina Del Rey💰 $170,000 - $230,000 / yearly
Apply Now →

Overview

Zefr is hiring a Manager of Machine Learning Operations to lead the ML Ops team and drive infrastructure for scalable machine learning systems. You'll work with technologies like Python and AI to optimize ML models. This position requires experience in managing ML operations and infrastructure.

Job Description

Who you are

You have a strong background in machine learning operations and infrastructure management — you've successfully led teams in deploying and optimizing ML models at scale. Your expertise in AI technologies allows you to bridge the gap between research and production effectively.

With a solid understanding of data engineering principles, you ensure that robust ML pipelines are built and maintained — your experience includes working with large datasets and ensuring model reliability in production environments. You are passionate about implementing best practices for model lifecycle management and have a keen interest in scalable ML infrastructure.

You possess excellent collaboration skills, enabling you to work closely with ML Engineers and Data Scientists — you understand the importance of teamwork in driving successful outcomes in machine learning projects. Your leadership style fosters an inclusive environment where diverse perspectives are valued.

Desirable

Experience with cloud platforms such as AWS or GCP is a plus — familiarity with tools like Docker and Kubernetes can enhance your contributions to the team. A background in software engineering principles will help you in overseeing the technical aspects of ML operations.

What you'll do

As the Manager of Machine Learning Operations, you will lead a team responsible for the deployment, monitoring, and optimization of ML models — your role will involve overseeing the infrastructure and tooling that support these systems. You will ensure that the ML models process multi-terabytes of data efficiently from various social media platforms.

You will collaborate with cross-functional teams to implement best practices for model lifecycle management — your leadership will guide the team in building and maintaining robust ML pipelines. You will also be responsible for driving the optimization of ML models to enhance performance and reliability in production.

In this role, you will have the opportunity to shape the future of Zefr's machine learning capabilities — your contributions will directly impact the company's ability to provide precise and transparent brand safety solutions. You will mentor team members and foster a culture of continuous improvement and innovation.

What we offer

Zefr provides a dynamic work environment where you can make a significant impact on the company's mission — you will be part of a team that values diversity and inclusion. We offer competitive compensation and benefits, along with opportunities for professional growth and development. Join us in powering responsible marketing through advanced machine learning technologies.

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