Senior Machine Learning Ops Engineer

Hayden AI

Senior MLOps Engineer focusing on building and deploying scalable AI/ML infrastructure at Hayden AI. Collaborating with cross-functional teams to enhance machine learning systems.

Posted 7/9/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $200,000 - $260,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformLinuxPython

About the role

Key responsibilities & impact

Architect, design, deploy, and operate scalable cloud-based MLOps platforms and workflows that enable efficient training, evaluation, deployment, monitoring, and lifecycle management of AI/ML models.
Own the technical strategy and evolution of ML infrastructure, identifying architectural bottlenecks and driving cross-functional initiatives to improve developer productivity, experimentation velocity, scalability, and operational efficiency.
Build robust, reliable, and automated systems that enable teams to ship new models and features rapidly while maintaining high standards for quality, reproducibility, observability, security, and production reliability.
Define and implement infrastructure optimization strategies that balance performance, scalability, reliability, and cost across cloud and compute resources.
Evaluate emerging tools, technologies, and industry best practices in MLOps, cloud infrastructure, and ML systems, and lead their adoption where they can meaningfully improve ML development and production workflows.
Establish engineering best practices for ML infrastructure, including system design, code quality, testing, CI/CD, monitoring, documentation, and operational readiness.
Provide technical leadership and mentorship to engineers, lead design and code reviews, and help raise the engineering quality and technical capabilities of the broader team.
Partner closely with ML engineers, researchers, data engineers, and product teams to translate evolving AI/ML requirements into scalable and maintainable infrastructure solutions.
Drive complex, ambiguous infrastructure projects from technical strategy and architecture through implementation, production deployment, and long-term operational ownership.

Requirements

What you’ll need

A Bachelors Degree or a Masters Degree in Computer Science, Electrical Engineering, or a related field.
Core Skills: General Software Engineering skills with 6+ years of programming experience in python and the surrounding tooling ecosystem along with familiarity in linux and expertise in infrastructure, cloud and/or MLOps.
Personal Attributes: Team player, good communication skills, self-starter.
Strong teamwork and communication skills to collaborate with cross-functional teams, including ML and software engineers.
Nice to Have: Experience building MLOps pipelines for deep learning based perception solutions on AWS or GCP

Benefits

Comp & perks

Options for medical, dental, and vision coverage for employees and dependents (for US employees)
Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)
401(k) with 3% company matching
Unlimited PTO
Daily catered lunches in our San Francisco office

ATS Keywords

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Hard Skills & Tools

Software EngineeringInfrastructure OptimizationML Model DeploymentAutomated Systems DevelopmentMonitoring and Observability

Soft Skills

Team PlayerGood Communication SkillsSelf-Starter