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.
