ML Ops Engineer For Media Platform

The Opportunity

Come help build the new cloud storage, compute, and AI/ML platform that is powering Adobe's next generation of professional video creation tools. This platform has machine learning and generative technologies at its core, and is enabling our customers to creatively and productively work with video in ways they never could before.

You will join a team of engineers with extensive backgrounds in infrastructure and distributed systems, media processing, and machine learning. You will be responsible for creating, scaling, and operating infrastructure that handles media storage and compute on a global scale.

Impact You'll Make

You will be instrumental in ensuring that our infrastructure is reliable, scalable, efficient, and secure. You will have the opportunity to both delight our customers with fast, always-available delivery of Adobe's groundbreaking technologies, and save our company money by reducing compute and storage costs.

Key Responsibilities

• Architect, build, and operate Kubernetes-based infrastructure for ML and media compute
• Manage usage of cloud (AWS, Azure, GCP) storage, database, and key-value-store systems, ensuring they deliver efficient performance
• Configure and monitor our platform's connections to third-party APIs for media processing
• Automate deployment, monitoring, and incident response for AI-powered applications
• Collaborate with engineering, product, and ML research teams to optimize workflows and infrastructure for rapid iteration
• Implement infrastructure-as-code and configuration management best practices
• Ensure compliance with security and privacy standards across environments
• Drive continuous improvement in reliability, performance, and developer productivity
• Troubleshoot and resolve infrastructure issues in production and development environments

Qualifications

• 5+ years of experience in ML Ops, DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles
• Deep expertise with cloud platforms (Azure, AWS, GCP) and container orchestration (Kubernetes, Docker)
• Proven experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, etc.)
• Experience with infrastructure-as-code development approaches (Terraform, etc.)
• Strong scripting and automation skills (Python, Bash, etc.)
• Experience supporting AI/ML workloads and data pipelines
• Familiarity with monitoring, logging, and alerting tools (Prometheus, Grafana, Splunk, Datadog, LK, etc.)
• Solid understanding of security, compliance, and privacy in cloud environments
• Excellent collaboration and communication skills
• Startup mentality: thrive in fast-paced, iterative environments

Nice to Have

• Experience with media processing, audio/video codecs, and audio/video container formats
• Experience with TypeScript and Node.js
• Experience with build systems such as Bazel
• Contributions to open-source DevOps or cloud infrastructure projects

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $164,600 -- $313,300 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

In California, the pay range for this position is $216,400 - $313,300

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law.

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