Machine Learning Operations Engineer

At PGE, our work involves dreaming about, planning for, and realizing a smarter, cleaner, more enduring Oregon neighborhood. Its core to our DNA and we haven't stopped since we started in 1888. We energize lives, strengthen communities and drive advancements in energy that promote social, economic and environmental progress. We're always on the lookout for people passionate about leading and being a part of teams that are advancing innovative clean energy solutions that are also affordable and accessible to all.

Summary

The Advanced Energy Delivery Technology Solutions (AEDTS) team at Portland General Electric plays a crucial role in advancing our clean energy future through smart grid technology. We operate in two key areas:

1. Horizontal: Serving enterprise-wide needs with AWS Cloud Data Lake, API management, data science, applications, and data products.

2. Vertical: Supporting specific AED applications like the Outage Management System (OMS) and ARCOS Callout System.

This dual approach enables the team to drive PGE's goals of decarbonization, electrification, and operational efficiency across the organization while also maintaining critical systems for reliable service delivery.

Our team is seeking a skilled Machine learning operations (ML ops) engineer with Dev Ops, Data ops experience to develop, enhance and support our data science models and workflows. The ideal candidate will have a strong background in cloud technologies, containerization, and automation, with a focus on applying these skills to machine learning environments.

Career Level Summary

Application Administrator 6011

Grade 7

Career Level: P3

• Requires in-depth knowledge and experience.

• Uses best practices and knowledge of internal or external business issues to improve products or services.

• Solves complex problems; takes a new perspective using existing solutions.

• Works independently, receives minimal guidance.

• Acts as a resource for colleagues with less experience.

Key Responsibilities

Application Administrator 6011 (P3)

Application Support (ASUP):

• Maintains application support processes and ensures all requests for support are handled per agreed procedures.

• Uses application management software and tools to investigate issues, collect performance statistics, and create reports.

Configuration Management (CFMG):

• Maintains secure configurations and applies tools, techniques, and processes to identify, track, log, and maintain accurate and current information.

Problem Management (PBMG):

• Initiates and monitors actions to investigate and resolve problems in systems, processes, and services.

• Determines problem fixes and assists with implementing preventative measures.

Incident Management (USUP):

• Prioritizes and diagnoses incidents, escalating unresolved issues when necessary.

• Facilitates recovery following incident resolution and ensures incidents are properly documented.

Porting/Software Configuration (PORT):

• Configures software and equipment, tests platform-specific versions of software, and identifies potential improvements based on outcomes.

Systems Design (DESN):

• Recommends/designs systems structures that meet business needs while considering performance and security requirements.

• Translates logical designs into physical designs and produces detailed documentation.

Machine learning operations (ML Ops)/ Dev Ops/ Data Ops:

• Develop and maintain CI/CD pipelines for machine learning models.

• Automate model deployment, monitoring, and scaling processes.

• Implement and manage version control for code, data, and models.

• Ensure data quality, security, and compliance throughout the ML lifecycle.

• Collaborate with data scientists, engineers, and other stakeholders.

• Optimize infrastructure for ML workloads.

• Troubleshoot and resolve issues in production ML systems.

• Implement logging, monitoring, and alerting for ML pipelines.

• Manage and optimize cloud resources for ML/AI workloads.

• Facilitate knowledge sharing and best practices across teams.

Qualifications

Education/Experience/Certifications

Application Administrator 6011 (P3):

• Requires a bachelor's degree in business, computer science, engineering, management, or another related field, or equivalent experience.

• Typically five or more years in a related field.

Competencies

Functional Competencies:

• Intermediate/Advanced knowledge of change-management processes.

• Intermediate/Advanced knowledge of lifecycle planning of configuration items (CI).

• Intermediate/Advanced knowledge of operating systems (e. g. , Unix, Windows).

• Intermediate/Advanced knowledge of database concepts.

• Intermediate/Advanced knowledge of certificate management.

• Intermediate/Advanced knowledge of infrastructure concepts.

• Intermediate/Advanced knowledge of service continuity planning and support.

Technical Competencies:

• Programming languages: Python or similar

• DevOps tools: Docker, Kubernetes, Jenkins, GitLab CI, or Azure DevOps

• Cloud platforms: AWS, Azure, or Google Cloud Platform (AWS preferred)

• Infrastructure as Code: Terraform, Ansible, or CloudFormation

• ML frameworks: TensorFlow, PyTorch, or scikit-learn

• Big data technologies: Spark, Hadoop, or Kafka

• Monitoring and logging: ELK stack or similar

• Version control: Git

• Database management: SQL and NoSQL databases

• Data pipeline tools: Airflow, Kubeflow or similar

• Containerization and orchestration

• CI/CD methodologies and tools

• Understanding of ML algorithms and model serving

• Knowledge of data privacy and security best practices

• Familiarity with MLOps principles and tools (e. g. , MLflow, DVC)

General Competencies:

• Advanced customer-focus skills.

• Advanced accuracy skills.

• Advanced risk management skills.

• Advanced oral and written communication skills.

• Advanced interpersonal skills.

• Advanced decision-making skills.

• Advanced organization and prioritization skills.

• Advanced meeting facilitation skills.

• Advanced team-building skills.

Physical, Schedule/Attendance and Cognitive Demands

Cognitive Level: Substantial: Consistent use of logic or scientific thinking to define problems, collect information, establish facts, and draw valid conclusions (for example, engineer, HR d.