Manager, Machine Learning Operations – Delivery

Robert Half

. Design and implement end-to-end machine learning operational solutions, including cloud infrastructure, model deployment, performance optimization, and security monitoring of ML models in production .

Posted 10/13/2026full-timeRemote • California • United StatesMid-LevelSenior💰 $115,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing end-to-end machine learning operational solutions, with a strong focus on cloud infrastructure, model deployment, and performance optimization. Proven leadership in managing high-performing teams and ensuring adherence to technical, security, and compliance standards.

Highest-signal resume keywords

Machine Learning EngineeringML Ops Best PracticesCloud Technologies (AWS, Azure)Data Pipeline ManagementTeam Leadership

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Applicant Tracking System Keywords

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Hard Skills

JavaJavaScriptPythonDockerTerraformAPI DevelopmentCI/CD AutomationData Infrastructure ManagementNetwork Technologies (VPCs)QA Test Automation

Soft Skills

Excellent Communication Skills

Tools & Technologies

RunScopeJMeterSecrets ManagerCode PipelineCode BuildCode Deploy

Industry Keywords

Disaster RecoveryBusiness ContinuityRecord RetentionData PrivacyModel Governance

Tech Stack

Tools & technologies

AWSAzureCloudDockerJavaJavaScriptJMeterPythonTerraform

About the role

Key responsibilities & impact

Design and implement end-to-end machine learning operational solutions, including cloud infrastructure, model deployment, performance optimization, and security monitoring of ML models in production
Lead and develop a team of ML engineers, Data Engineers, Software Engineers, and DevOps specialists
Partner with cross-functional teams to integrate ML and cloud technologies into products and services
Implement and enforce ML Ops best practices, including continuous integration, continuous delivery, automated testing, security by design, and scalable infrastructure solutions
Drive the use of cloud technologies and services for ML model training and deployment, optimizing performance and cost
Own development and maintenance of data pipelines for data ingestion, processing, and model training
Lead the department’s efforts within enterprise Disaster Recovery, Business Continuity, and Record Retention initiatives
Evaluate and integrate advancements in ML Ops, DevOps, SecOps, and Cloud Infrastructure and Architecture
Ensure adherence to technical, security, and compliance standards, including infrastructure security, data privacy, and model governance

Requirements

What you’ll need

Bachelor's degree (B.S. or higher) in Computer Science, Engineering, Mathematics, a related STEM field or equivalent work experience; M.S. preferred
3+ years of experience managing high-performing software development teams, with 5+ direct reports
2+ years of experience working closely with, or 1+ year of experience managing, Platform Engineering teams
6+ years deploying Java, JavaScript, and Python solutions
3+ years of experience in machine learning engineering, with a proven track record of deploying and managing ML models in production environments
Expertise in ML Ops, DevOps practices, and API development
3+ years of experience managing data infrastructure and data pipelines
3+ years of experience building and supporting serverless multi-cloud deployment and provisioning using AWS and Azure
3+ years of experience building and deploying Docker solutions
3+ years of experience designing and deploying advanced Terraform solutions
3+ years of experience in network technologies (VPCs)
Prior experience developing and maintaining Disaster Recovery Operational Recovery Documents and Business Continuity plans
1+ years of experience using RunScope, JMeter and Secrets Manager to manage sensitive assets
1+ years of experience with QA Test Automation and CI/CD automation using Code Pipeline, Code Build and Code Deploy
1+ years of experience with Git Hooks and managing pre-commit validation
Familiarity designing and implementing Terraform infrastructure
Familiarity with AWS and Azure budget management
Excellent communication skills, capable of conveying complex technical concepts to diverse audiences
Experience implementing agentic operations at scale is highly desirable
Experience with vector databases, relational databases, NLP model deployment, and analysis of large datasets is highly desirable
Experience with clustering, dimensionality reduction, and language model deployment is a plus
Experience with Record Retention policies and initiatives is a plus
Ability to complete a successful background check

Benefits

Comp & perks

Group health insurance benefits (medical, vision, dental)
FSA and HSA healthcare accounts
Life and accident insurance
Adoption and fertility assistance
Paid parental leave of up to 6 weeks
Short-term and long-term disability
Paid time off for vacation, personal needs, and sick time
Choice Time Off (CTO), up to 17 days per calendar year for new hires
Up to 11 paid holidays per calendar year
401(k) savings and investment plan or deferred compensation plan (if eligible)
Employer match of 100% on the first 3% of contributions for eligible employees
Discretionary annual bonus
Reasonable accommodation assistance for applicants with disabilities