Manager, Machine Learning Operations (MLOps)

What We Do:

Zefr is the global leader in brand suitability targeting and measurement across the world's largest platforms. Zefr's technology is helping to power the age of responsible marketing by putting advertisers in control of their content adjacencies based on their own unique brand safety and suitability preferences. As an official YouTube Measurement Program Partner, Meta for Business Partner, and TikTok for Business Partner, the company leverages patented machine learning and AI technology (Cognition AI) to offer brands and agencies more precise and transparent brand safety and suitability activation and measurement solutions on scaled platforms. The company is headquartered in Los Angeles, California, with additional locations across the globe.

What You'll Do:

We are hiring a Manager of Machine Learning Operations to lead our ML Ops team and drive the infrastructure, tooling, and processes that enable our machine learning systems to operate at scale. You will oversee the deployment, monitoring, and optimization of ML models that process multi-terabytes of social media platform data from TikTok, YouTube, Facebook, Instagram, and Snap. In this role, you will lead a team of engineers responsible for building and maintaining robust ML pipelines, ensuring model reliability in production, and implementing best practices for model lifecycle management. You will collaborate closely with ML Engineers and Data Scientists to bridge the gap between research and production. We are excited to welcome a leader who is passionate about building scalable ML infrastructure and developing high-performing teams.

Key Responsibilities:

Lead, mentor, and grow a team of Machine Learning Engineers, fostering a culture of innovation and continuous improvement

Design and implement scalable ML infrastructure for model training, deployment, and serving

Establish and enforce best practices for ML model lifecycle management, including versioning, testing, and monitoring

Develop and maintain CI/CD pipelines for machine learning workflows

Optimize model inference performance and reduce latency/cost across production systems

Collaborate with ML Engineers and Data Scientists to productionize models efficiently

Implement robust monitoring, alerting, and observability solutions for ML systems

Drive technical decisions on ML Ops tooling, infrastructure, and architecture

Ensure high availability and reliability of ML services at scale

Manage project timelines, priorities, and resource allocation for the ML Ops team

Tech Stack:

Languages: Python, SQL

Data Stores: Snowflake, Qdrant, GCS

Data Processing: DBT, Pandas, Ray

DevOps: GitHub Actions, Docker, Terraform, Kubernetes, ArgoCD, AWS, GCP, Datadog

MLOps: Triton Inference Server, Weights and Biases, ONNX, TensorRT LLM, vLLM, SGLang

ML: Voxel51 Teams, Transformers, PyTorch, HuggingFace

What We're Looking For:

Bachelor's or Master's degree in Computer Science or related field with 5+ years of professional experience in ML Engineering or MLOps

1+ years of experience leading or guiding engineering teams in either formal or informal leadership roles

Deep expertise in ML model deployment, serving infrastructure, and production ML systems

Hands-on experience with transformer architectures (e.g., BERT, ViT) for natural language and vision tasks.

Strong understanding of multimodal embedding techniques for integrating text, image, audio, and structured data.

Experience with LLM models such as Gemini, GPT, Claude, Qwen, etc.

Experience with ML experiment tracking, model versioning, and feature stores

Strong understanding of CI/CD principles applied to ML workflows

Experience optimizing model inference performance (ONNX, TensorRT, or similar)

Excellent leadership, communication, and stakeholder management skills

Track record of building and scaling high-performing engineering teams

Openness to new technologies and creative solutions

Nice to Have:

Experience with ad tech and digital advertising ecosystem

Experience with multimodal LLM fine-tuning

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

14 paid holidays off

Flexible hybrid work schedule

"Summer Fridays" (shorter work days on select Fridays during the summertime)

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 base salary for this position is between $170,000 and $230,000. 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 b