SRE / MLOps Engineer

Description

We are seeking a versatile SRE / MLOps Engineer with DevSecOps expertise to design, automate, and operate secure, scalable, and repeatable model deployment workflows across the AI / ML Common Services environment. This role bridges infrastructure reliability, CI / CD automation, and model operations , enabling IRS mission teams to move from experimentation to production with confidence.

The engineer will not only support ML lifecycle operations (Databricks, MLflow, AWS SageMaker / Bedrock) but also bring DevSecOps rigor to ensure compliance, monitoring, and infrastructure-as-code are embedded in every step. By partnering with Infrastructure, Security, and Architecture teams, this role ensures the AAP environment is resilient, automated, and compliance-ready at enterprise scale.

Key Responsibilities

• Enable secure, scalable, and repeatable deployment workflows for both ML models and supporting infrastructure.
• Build and maintain runtime environments, service accounts, orchestration logic for Databricks, MLflow, and AWS AI services.
• Implement and maintain CI / CD pipelines (Bitbucket, Bamboo, Jenkins, or equivalent) for code, data, and model deployments.
• Apply DevSecOps practices — integrating security scans, compliance checks, and audit logging into deployment pipelines.
• Collaborate with Infrastructure DSO and Solutions Architect to integrate Terraform-based IaC for consistent, automated provisioning.
• Implement observability, alerting, and logging (CloudWatch, Datadog, Prometheus) to monitor both application and ML workloads.
• Align infrastructure with ML lifecycle needs — including staging, promotion, rollback, retraining, and compliance-aware tracking.
• Develop automation templates, reusable workflows, and guardrails to accelerate onboarding of mission team models while ensuring security.
• Contribute to incident response, performance tuning, and reliability engineering across ML and non-ML workloads.

Qualifications

Required Qualifications

Desired Skills

Databricks Certified Machine Learning Professional.

Target salary range : $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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