AI/ML Engineer in Calgary

Join the dynamic and collaborative team at Katalyst Data Management (KDM)! KDM is seeking an AI/ML Engineer to support the operation, optimization, and reliability of the infrastructure powering our AI innovation platform. This hands-on role will help maintain GPU environments, monitor large-scale data ingestion and document processing pipelines, support DevOps and platform operations, and contribute to scalable AI/ML solutions that deliver real value to global energy clients.

The ideal candidate brings practical experience in systems administration, DevOps, MLOps, or software engineering; strong problem-solving skills; and the curiosity and adaptability to learn new tools quickly in a fast-moving technical environment.

Key Responsibilities:

• Monitor, maintain, and optimize machine learning infrastructure, including test environments and production-grade NVIDIA GPU systems.
• Manage GPU workload allocation and balancing across services such as embedding generation, OCR processing, and inference pipelines.
• Establish and maintain system observability, including health metrics, alerting frameworks, and uptime targets for AI platforms.
• Identify and implement improvements to system efficiency, resource utilization, and pipeline performance.
• Diagnose and resolve hardware and system-level issues.
• Operate and monitor large-scale ingestion pipelines processing high-volume datasets.
• Manage preprocessing workflows for domain-specific data formats.
• Monitor, troubleshoot, and optimize OCR workflows.
• Develop and maintain dashboards, logging, and alerting mechanisms.
• Perform data validation and quality assurance checks on ingested content.
• Support CI/CD pipelines, automated testing frameworks, and release processes.
• Assist in the administration and optimization of Elasticsearch/OpenSearch clusters.
• Develop and maintain infrastructure documentation.
• Support and enhance containerized deployment environments using Docker.
• Partner with Senior AI/ML Engineers to support RAG pipeline development.
• Contribute to internal automation, scripting, and tooling.
• Participate in agile ceremonies.

Skills & Qualifications Required:

• Experience with Elasticsearch or OpenSearch administration in production environments.
• Strong familiarity with AWS services.
• Experience with monitoring and observability tools.
• Working knowledge of CI/CD pipelines and tools.
• Experience supporting NVIDIA GPU environments.
• Familiarity with OCR technologies and document processing pipelines.
• Proficiency with Git/version control systems.
• Experience supporting production AI, data, or search platforms.
• Interest in or familiarity with the oil and gas / energy domain is an asset.
• Strong English communication skills, both oral and written, are required.

Preferred Qualifications & Skills:

• Oil and gas industry experience or domain knowledge.
• Experience with GPU-accelerated workloads.
• Background in OCR pipelines and large-scale document processing.
• Familiarity with vision-language models for document understanding.
• Patent, publication, or conference presentation experience in ML/AI.

Required Education and Experience:

• 1–3 years of professional experience in DevOps, systems administration, MLOps, or software engineering.
• Basic understanding of machine learning concepts.
• Hands-on experience with Linux workstations or servers.
• Experience deploying and managing containerized applications using Docker.
• Proficiency in scripting with Python and/or Bash for automation and monitoring.

This role is based in a professional office setting with routine use of computers and collaboration tools. Work is highly technical and team-oriented, involving close coordination with Cloud, Infrastructure, and Software Engineering teams.

Physical Demands:

This is primarily a sedentary role, involving extended periods of computer work.

Position Type and Expected Hours of Work:

This is a full-time position. As a full-time position, the AI/ML Engineer is eligible to participate in benefits coverage offered to Katalyst employees based on geographical location.

Travel: Minimal travel may be required for on-premises infrastructure support, implementation, or occasional team collaboration.