Senior AI/ML Engineer (Remote) — Utility AI Solutions

Kibbi Technologies Inc.; Calgary; On-site; CAD 161,000 - 202,000; Full time

Benefits offered by this job

Medical, dental, vision

Life insurance

Disability coverage

Remote work

401(k) match

Flexible time off

Job summary

E Source is seeking a Senior AI/ML Engineer to join a team delivering cutting-edge ML and AI products for the utility sector. You will design scalable ML pipelines, build reusable Python packages, and integrate advanced AI systems, including RAG and agent-based workflows.

You will work with data scientists and software engineers, shape ML lifecycle management, and contribute to an agile, remote-friendly environment.

Qualifications

• Master’s degree or higher in a related field.
• 7+ years of professional ML software development experience.
• Strong Python programming and packaging skills.

Responsibilities

• Collaborate with cross-functional teams to design and deploy scalable ML/AI products.
• Build reusable Python packages and data-processing pipelines.
• Design AI systems including RAG, LLM integration, and agent-based workflows.
• Develop evaluation/monitoring frameworks for model reasoning and fairness.
• Evaluate database design and optimize data processing and retrieval.
• Translate complex ML tasks into actionable user and technical stories.
• Ensure high-quality test coverage and participate in code reviews.
• Stay current with ML/AI advances and integrate best practices.

Skills

Python

Databricks

ML systems design

MLOps

Cloud platforms

CI/CD pipelines

Distributed computing

Generative AI tools

Agentic AI / AI orchestration

Communication & collaboration

Education

Master's degree in CS/SE/DS

PhD preferred

Tools

Databricks stack

LangChain

Hugging Face

LlamaIndex

AutoGen

Job description

E Source is seeking a Senior AI/ML Engineer to join a team delivering cutting-edge ML and AI products for the utility sector. You will design scalable ML pipelines, build reusable Python packages, and integrate advanced AI systems, including RAG and agent-based workflows.

You will work with data scientists and software engineers, shape ML lifecycle management, and contribute to an agile, remote-friendly environment.