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Technical Product Manager, AI/ML

What We Do:

Zefr is the leading global technology company enabling responsible marketing in walled garden social environments. Zefr’s solutions empower brands to manage their content adjacency on scaled platforms such as YouTube, Meta, TikTok, and Snap, in accordance with industry standard frameworks. Through its patented AI technology, Zefr offers brands and agencies more accurate and transparent solutions for social walled gardens. The company is headquartered in Los Angeles, California, with additional locations across the globe.

What You’ll Do:

As a Technical Product Manager specializing in machine learning infrastructure, you will play a key role in defining the strategy and execution for our ML inference pipeline and internal tooling. You will work closely with data scientists, ML engineers, and infrastructure teams to deliver scalable, high-performance ML solutions.

What You’ll Be Responsible for:

Inference Pipeline Management:

  • Own and manage the end-to-end ML inference pipeline, ensuring low latency, high reliability, and scalability.

  • Define and drive the strategy to improve model performance, deployment, and monitoring with a focus on minimizing costs and maximizing efficiency through collaboration with engineering and data science teams.

  • Develop a strategy for cost-effective model inference, including identifying bottlenecks and opportunities to reduce compute and infrastructure expenses.

Support Tooling:

  • Lead the development of internal tools to improve model monitoring, health checks, and logging.

  • Oversee development of  Internal Tools to enable Sales and Customer Success to showcase the value of Zefr AI

  • Define the strategy and requirements for automated solutions that improve data labeling, model retraining, and performance evaluation, working closely with engineering to drive implementation.

  • Build self-service tools that empower engineers and data scientists to troubleshoot and deploy models independently.

  • Support integrations with third-party vendors to augment ML workflows.

How You’ll Do It:

  • Partner with data scientists, ML engineers, infrastructure, and customer success teams to ensure seamless deployment and monitoring.

  • Manage product backlogs and ensure timely delivery of key milestones.

  • Lead engineering ceremonies, including stand-ups, grooming, planning, and retrospectives.

  • Serve as the primary point of contact for product updates, strategy changes, and performance insights.

  • Translate technical concepts and performance data into actionable insights for business stakeholders.

  • Work with customer success teams to address customer pain points and improve satisfaction.

  • Provide leadership in incident response for inference and tooling issues, ensuring quick resolution and learning from post-mortems.

What We’re Looking For:

  • 5+ years of experience in software engineering, machine learning engineering, or a similar technical field - bonus if you’ve got experience as a technical product manager

  • Excellent written and verbal communication skills, with the ability to explain technical concepts (especially complex ML/AI concepts) to a variety of audiences, ranging from highly technical to very non-technical.

  • Strong technical background (degree in Computer Science, Engineering, or related field preferred).

  • Experience with machine learning infrastructure, inference pipelines, and cloud-based deployment (Google Cloud, AWS, or Azure).

  • Strong SQL skills, with experience in querying large datasets and building data pipelines.

  • Hands-on experience with ML frameworks like TensorFlow and PyTorch.

  • Strong problem-solving skills and a data-driven approach to decision-making.

Preferred Qualifications:

  • Experience with real-time inference and large-scale model deployment.

  • Experience as a technical product manager or technical program manager.

  • Familiarity with vector search, embeddings, and NLP models.

  • Experience building internal developer platforms and self-service tooling.

  • Experience with labeling platforms

  • Strong understanding of machine learning monitoring frameworks and observability tools.

  • Experience with Machine Learning Operations, specifically model lifecycle management. 

Why Join Us?

  • Be part of a cutting-edge AI and ML platform driving the future of brand safety and sentiment analysis.

  • Work with a collaborative and talented team of engineers, data scientists, and product managers.

  • Opportunity to define the technical strategy and build foundational infrastructure for a high-impact product.

Benefits (for US based employees):

  • Flexible PTO

  • Medical, dental, and vision insurance with FSA options

  • Company-paid life insurance

  • Paid parental leave

  • 401(k) with company match

  • Professional development opportunities

  • 10+ paid holidays off

  • Summer Fridays (we leave early)

  • Flexible hybrid work schedule

  • In-office lunches and lots of free food

  • Optional in-person and virtual events (we like to celebrate!)

Compensation (for US based employees):

The anticipated salary for this position is between $140,000 and $160,000.   Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training. If your compensation expectations fall outside of this range, it may still be worth having a conversation.

Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace. We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better.  We strongly encourage women, persons of color, LGBTQIA+ individuals, persons with disabilities, members of ethnic minorities, foreign-born residents, and veterans to apply even if you do not meet 100% of the qualifications.

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CEO of ZEFR
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Zach James and Rich Raddon
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What You Should Know About Technical Product Manager, AI/ML, ZEFR

At Zefr, we're on a mission to redefine responsible marketing in social environments using cutting-edge technology, and we're looking for a Technical Product Manager, AI/ML to join our innovative team in beautiful Marina del Rey. In this exciting role, you will be at the forefront of our machine learning infrastructure, managing our ML inference pipeline and ensuring that we deliver high-performance solutions that help brands thrive in walled gardens like YouTube, Meta, and TikTok. You'll collaborate with a diverse group of data scientists and engineers, driving projects that enhance model performance while keeping an eye on efficiency and costs. You'll have the chance to develop internal tools that improve monitoring and integration, empowering our Sales and Customer Success teams to showcase the true value of Zefr AI. Your strategic thinking will lead to the creation of self-service tools that give our tech teams the autonomy to troubleshoot and deploy models independently, ensuring we stay ahead in a fast-paced industry. With a supportive, agile team, you'll help shape our product strategy and be the go-to person for performance insights and customer satisfaction initiatives. Come and be part of our adventure to build a groundbreaking AI platform, where your work directly influences our success and drives the future of brand safety.

Frequently Asked Questions (FAQs) for Technical Product Manager, AI/ML Role at ZEFR
What are the top responsibilities of a Technical Product Manager, AI/ML at Zefr?

As a Technical Product Manager specializing in AI/ML at Zefr, your key responsibilities will include managing the end-to-end ML inference pipeline, driving improvements in model performance, overseeing the development of internal tools, and collaborating closely with cross-functional teams. You’ll focus on ensuring low latency, high reliability, and scalability while helping to define strategies for cost-effective model inference.

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What qualifications are required for the Technical Product Manager, AI/ML role at Zefr?

To thrive as a Technical Product Manager, AI/ML at Zefr, you should have over 5 years of experience in technical fields such as software engineering or machine learning, excellent communication skills to convey complex concepts, and a solid understanding of ML infrastructure and cloud deployments. A degree in Computer Science or a related field, along with experience with ML frameworks and strong SQL skills, is also essential.

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How does the Technical Product Manager, AI/ML position contribute to Zefr's mission?

The Technical Product Manager, AI/ML at Zefr plays a crucial role in enhancing our machine learning capabilities, which directly impacts how brands manage their content adjacency. By developing effective inference pipelines and tools, you help provide accurate and transparent solutions, making a significant contribution to our mission of promoting responsible marketing strategies.

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What kind of team culture can a Technical Product Manager expect at Zefr?

At Zefr, the culture is collaborative and innovative, emphasizing support and teamwork. As a Technical Product Manager, you will work alongside talented engineers, data scientists, and product managers who are passionate about AI and ML, fostering an environment where ideas are welcomed, and autonomy is encouraged.

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What opportunities for professional development does Zefr offer for a Technical Product Manager, AI/ML?

Zefr is committed to the growth of its employees, offering various professional development opportunities such as workshops, courses, and events to enhance your skills and knowledge in AI and machine learning. As a Technical Product Manager, you’ll also have the chance to define technical strategies that can propel your career forward.

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Common Interview Questions for Technical Product Manager, AI/ML
How do you prioritize tasks as a Technical Product Manager?

When prioritizing tasks, I assess the impact on overall product goals, aligning them with team capacity and stakeholder needs. I use frameworks like MoSCoW or RICE to classify tasks, ensuring that high-impact items are prioritized while maintaining flexibility to adjust as needed.

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Can you describe a challenging project you managed and how you overcame obstacles?

In a past project, I faced delays due to integration challenges with ML models. I organized a series of meetings with engineering and data science teams to identify bottlenecks and implemented agile methodologies to expedite development and ensure we met our deadlines.

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How do you measure the success of an ML product?

Success can be measured using key performance indicators such as model accuracy, inference speed, user engagement, and customer feedback. Constantly monitoring these metrics allows for iterations and improvements, ensuring the product continually meets user needs.

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What experience do you have with machine learning frameworks?

I have hands-on experience with TensorFlow and PyTorch, developing models from conception through deployment. I'm comfortable using these frameworks for various ML tasks, and I understand the intricacies of integrating them into production environments.

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How do you communicate technical information to non-technical stakeholders?

I simplify complex concepts using analogies and visual aids, focusing on how the technical details relate to business outcomes. I encourage questions to ensure clarity and foster an environment where stakeholders feel comfortable engaging with technical content.

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What strategies do you use for stakeholder management?

Regular communication, transparency about project timelines, and actively involving stakeholders in the decision-making process are key strategies I employ. I make it a priority to address concerns early, ensuring all parties feel valued and informed throughout the development cycle.

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Describe your experience with cloud-based deployments.

I have extensive experience deploying ML models on platforms like Google Cloud and AWS, focusing on scalability and cost efficiency. I also emphasize best practices in security and compliance to ensure robust deployment processes.

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How do you keep up to date with advancements in AI/ML?

I regularly attend conferences, participate in webinars, and follow leading researchers and institutions in AI/ML. Engaging with the community through forums and online courses also helps me stay current with emerging trends and technologies.

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What is your approach to improving ML model performance?

To improve model performance, I analyze data for quality and relevance, tweak algorithm parameters, and incorporate feature engineering techniques. Regular evaluations and comparisons against baseline models help in identifying opportunities for enhancement.

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How would you support the Customer Success team as a Technical Product Manager?

I would provide them with data-driven insights and tools that enable them to showcase our product’s value. Additionally, I would work closely with them to gather feedback from clients, using that information to inform future product improvements.

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Full-time, hybrid
DATE POSTED
March 17, 2025

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