ML Ops Engineer at Adobe

San Jose, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

TechnologyIndustries

Requirements

3–5+ years in MLOps, DevOps, or ML platform engineering
Strong experience with cloud infrastructure (AWS/GCP/Azure), container orchestration (Kubernetes), and IaC tools (Terraform, Helm)
Familiarity with ML model serving tools (e.g., MLflow, Seldon, TorchServe, BentoML)
Proficiency in Python and CI/CD automation (e.g., GitHub Actions, Jenkins, Argo Workflows)
Experience with monitoring tools (Prometheus, Grafana, Datadog, ELK, Arize AI, etc.)
Bachelor's or equivalent experience in Computer Science, Engineering, or a related technical field
Preferred Qualifications
Experience supporting LLM applications, RAG pipelines, or AI agent orchestration
Understanding of vector databases, embedding workflows, and model retraining triggers
Exposure to privacy, safety, and responsible AI principles in operational contexts

Responsibilities

Manage model versioning, deployment strategies, rollback mechanisms, and A/B testing frameworks for LLM agents and RAG systems
Coordinate model registries, artifacts, and promotion workflows in collaboration with ML Engineers
Implement real-time monitoring of model performance (accuracy, latency, drift, degradation)
Track conversation quality metrics and user feedback loops for production agents
Develop automated pipelines for timely/agent testing, validation, and deployment
Integrate unit/integration tests into model and workflow updates for safe rollouts
Provision and manage scalable infrastructure (Kubernetes, Terraform, serverless stacks)
Enable auto-scaling, resource optimization, and load balancing for AI workloads
Craft and maintain data ingestion pipelines for both structured and unstructured sources
Ensure reliable feature extraction, transformation, and data validation workflows
Monitor and optimize AI stack performance (model latency, API efficiency, GPU/compute utilization)
Drive cost-aware engineering across inference, retrieval, and orchestration layers
Build alerting and triage systems to identify and resolve production issues
Maintain SLAs and develop rollback/recovery strategies for AI services
Enforce model governance, audit trails, and explainability standards
Support documentation and regulatory frameworks (e.g., GDPR, SOC 2, internal policy alignment)

Skills

Kubernetes

Terraform

CI/CD

A/B Testing

Model Versioning

Model Deployment

Monitoring

LLM

RAG

Data Pipelines

Auto-scaling

Adobe

Software solutions for content creation and marketing

About Adobe

Adobe provides a range of software solutions focused on digital experiences, catering to creative professionals, businesses, and educational institutions. Its main offerings include Adobe Creative Cloud, which contains tools for photography, graphic design, video editing, illustration, UI/UX design, 3D and augmented reality, and social media content creation. Adobe also offers marketing solutions through Adobe Experience Cloud and document management services via Adobe Document Cloud. The company operates on a subscription-based model, allowing users to access its software through monthly or annual plans, with special pricing available for students, teachers, and businesses. Adobe differentiates itself from competitors by providing a comprehensive suite of tools that cover various aspects of content creation and marketing, all integrated into one platform. The goal of Adobe is to empower users to create, manage, and optimize their digital content effectively.

San Jose, CaliforniaHeadquarters

1994Year Founded

$668.9MTotal Funding

IPOCompany Stage

Consumer Software, Enterprise Software, DesignIndustries

10,001+Employees