Manager, Machine Learning Operations – MLOps

Zefr

Manager, Machine Learning Operations overseeing ML Ops team at Zefr. Leading infrastructure, tooling, and processes for scalable ML systems and model deployment.

Posted 4/28/2026full-timeMarina del Rey • California • 🇺🇸 United StatesMid-LevelSenior💰 $170,000 - $230,000 per yearWebsite

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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!)

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine Learning EngineeringMLOpsML model deploymenttransformer architecturesmultimodal embedding techniquesLLM modelsML experiment trackingmodel versioningfeature storesmodel inference optimization

Soft Skills

leadershipcommunicationstakeholder managementteam buildinginnovationcontinuous improvementproject managementresource allocationcollaborationtechnical decision-making

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer Science