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This listing was closed on Jul 18, 2026.
Browse Open JobsStaff MLOps Engineer – ML Platform
Summary by AIEngineer.careers
Staff MLOps Engineer – ML Platform is a MLOps Engineer role (full-time). with BrightAI. in PALO ALTO, US. Imported listing (source: linkedin.com). Apply on the employer's site (linkedin.com).
Imported listing (source: linkedin.com) · Apply on linkedin.com
PALO ALTO · US
—
Full-time
STAFF
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from linkedin.com
BrightAI is building a cloud-native ML developer platform on AWS. They are hiring a Staff MLOps Engineer to lead the design and operation of production ML pipelines, CI/CD for ML, and infrastructure-as-code. The role involves working with SageMaker, Docker, Terraform, and various AWS services to enable scalable ML workflows.
Responsibilities
- Design, build, and operate the ML/AI development platform on AWS including SageMaker, EKS, and supporting services
- Establish golden-path project templates, Docker images, and internal libraries to standardize ML workflows
- Implement Infrastructure-as-Code (Terraform) and workflow orchestration (Step Functions, Airflow)
- Build automated data pipelines with S3, Glue, EMR/Spark, Athena/Redshift
- Set up experiment tracking and model registry (SageMaker Experiments/MLflow)
- Implement CI/CD for ML with CodeBuild/CodePipeline or GitHub Actions
- Ship real-time endpoints and batch jobs with monitoring and autoscaling
- Enforce security and governance (IAM, VPC, encryption)
Requirements
- 8+ years in software/ML engineering, including 4+ years in MLOps
- Strong programming skills in Python
BrightAI
Palo Alto · US · 146+ employees
BrightAI is a technology company that provides a Physical AI platform for monitoring and managing essential critical infrastructure. Its solutions enable proactive asset management, predictive maintenance, and improved operational efficiency for industries such as water, energy, and manufacturing.
