Manager, Machine Learning Operations & Delivery

Robert Half • San Ramon, CA

21h • $115,000 - $175,000

About The Position

Robert Half’s Data Science Innovation team is seeking a hands-on, player-coach Manager to lead key initiatives in ML Operations & Delivery. The manager will orchestrate DevOps, ML Ops, infrastructure, security, and API development to support scalable machine learning solutions, while leading day-to-day ML efforts and contributing technically. The role is responsible for building robust, scalable ML systems and integrating them into product offerings.

The position leads a team of ML engineers, Data Engineers, Software Engineers, and DevOps specialists; collaborates with cross-functional teams; and drives cloud-based model training and deployment. It also leads the department’s work on enterprise disaster recovery, business continuity, and record retention, and ensures technical, security, privacy, compliance, and model-governance standards are met.

The typical annual salary range is $115,000–$175,000, negotiable based on experience and location. The position is eligible for a discretionary annual bonus. Employment offers are contingent on successful completion of a background check.

Requirements

• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, a related STEM field, or equivalent work experience; an M.S. is preferred.
• Strong leadership skills and ability to foster collaboration, inclusion, and innovation.
• At least 3 years managing high-performing software development teams, with 5 or more direct reports.
• At least 2 years working closely with Platform Engineering teams, or at least 1 year managing them.
• At least 6 years deploying Java, JavaScript, and Python solutions.
• At least 3 years of machine learning engineering experience, including deploying and managing ML models in production.
• Expertise in ML Ops, DevOps practices, and API development.
• At least 3 years managing data infrastructure and data pipelines.
• At least 3 years building and supporting serverless multi-cloud deployment and provisioning using AWS and Azure.
• At least 3 years building and deploying Docker solutions.
• At least 3 years designing and deploying advanced Terraform solutions.
• At least 3 years of experience with network technologies such as VPCs.
• Prior experience developing and maintaining Disaster Recovery Operational Recovery Documents and Business Continuity plans.
• Security-minded approach to API and data security, with at least 1 year using RunScope, JMeter, and Secrets Manager to manage sensitive team assets.
• At least 1 year of experience with QA test automation and CI/CD automation using Code Pipeline, Code Build, and Code Deploy.
• At least 1 year of experience with Git Hooks and managing pre-commit validation.
• Excellent communication skills and ability to convey complex technical concepts to diverse audiences.

Nice To Haves

• Experience working with or contributing to a Data Mesh.
• Experience implementing agentic operations at scale.
• Experience with vector databases, relational databases, NLP model deployment, and analysis of large datasets.
• Experience with clustering, dimensionality reduction, and language model deployment.
• Experience with Record Retention policies and initiatives.
• M.S. degree.
• Familiarity with designing and implementing Terraform infrastructure.
• Familiarity with AWS and Azure budget management.

Responsibilities

• Design and implement end-to-end machine learning operational solutions, including cloud infrastructure, model deployment, performance optimization, and production-model security monitoring.
• Lead and develop a team of ML engineers, Data Engineers, Software Engineers, and DevOps specialists, fostering innovation, high performance, and collaboration.
• 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.
• Drive the use of cloud technologies and services for ML model training and deployment, optimizing performance and cost.
• Own the development and maintenance of data pipelines for data ingestion, processing, and model training.
• Lead the department’s work within enterprise Disaster Recovery, Business Continuity, and Record Retention initiatives, ensuring alignment with requirements and timelines.
• Evaluate and integrate advancements in ML Ops, DevOps, SecOps, and cloud infrastructure and architecture.
• Ensure the team adheres to technical, security, and compliance standards in the ML domain, including infrastructure security, data privacy, and model governance.

Benefits

• Discretionary annual bonus.
• Group health insurance benefits, including medical, vision, and dental.
• FSA and HSA healthcare accounts.
• Life and accident insurance.
• Adoption and fertility assistance.
• Paid parental leave of up to 6 weeks.
• Short- and long-term disability insurance.
• Paid time off for vacation, personal needs, and sick time; new hires earn up to 17 days of Choice Time Off per calendar year, prorated based on hours worked per week and varying by years of service.
• Up to 11 paid holidays per calendar year.
• 401(k) savings and investment plan or deferred compensation plan, if eligible, with a 100% employer match on the first 3% of eligible employees’ contributions.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager