Lead ML Engineer – Cloud AI, MLOps & Agentic AI – AIRLHV

Lead ML Engineer – Cloud AI, MLOps & Agentic AI

NavitasPartners is hiring a Lead Machine Learning Engineer to spearhead enterprise AI projects from Calgary, Canada. This remote/hybrid contract or full‑time role focuses on building MLOps pipelines, GenAI, and next‑generation agentic AI systems in cloud environments.

Key Responsibilities

• Design, develop, and deploy scalable ML and Generative AI solutions on major cloud platforms.
• Architect end‑to‑end MLOps pipelines, automation frameworks, and CI/CD processes.
• Lead cross‑functional teams of data scientists, software engineers, and solution architects.
• Implement monitoring, logging, and governance for production AI models.
• Stay current with emerging AI technologies and integrate them into the product roadmap.

Required Skills & Experience

• 5+ years of hands‑on experience in machine learning engineering and MLOps.
• Proficiency with cloud services (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker).
• Strong programming skills in Python and familiarity with ML libraries such as TensorFlow, PyTorch, or JAX.
• Experience building and scaling GenAI or agentic AI systems.
• Solid understanding of CI/CD, Terraform/CloudFormation, and data pipeline tools (Airflow, Kubeflow).
• Excellent communication and leadership abilities.

Preferred Qualifications

• Master’s or PhD in Computer Science, AI, or related field.
• Hands‑on experience with large language models and prompt engineering.
• Knowledge of security, compliance, and model governance in regulated industries.

Location & Work Model

This role is based in Calgary, Calgary region, Canada, with flexibility for remote or hybrid work across the US and Canada.

Frequently Asked Questions

What type of employment is offered for the Lead ML Engineer position?

The role can be hired as a contract or full‑time position, with options for remote or hybrid work.

Which cloud platforms should candidates be experienced with?

Candidates should have proven experience with major cloud providers such as AWS, Azure, or Google Cloud.

Is prior experience with generative or agentic AI required?

Yes, experience designing, building, or deploying generative AI or agentic AI systems is required.