Senior Applied AI Engineer

clariticloudinc; United States; Remote; USD 105,000 - 126,000; Full time

Benefits offered by this job

Remote work

Travel 1–2x per year

Competitive CAD salary

Job summary

clariticloudinc is seeking a senior AI lead to drive applied AI across product teams, turning ML research into reliable features for unstructured data. The role covers computer vision, LLMs, agentic workflows, and multimodal learning, from problem framing to production deployment.

You will collaborate with product and engineering partners and leverage a research team for technical review, deploying, monitoring, and iterating models while balancing accuracy, latency, and cost.

Qualifications

• 7–10 years of hands-on applied AI or ML experience in industry.
• Experience leading AI work independently, incl. production deployment without a dedicated ML team.
• Practical MLOps experience: CI/CD, containers, deployment, monitoring.
• Ability to communicate technical decisions clearly across product, eng and non-technical groups.
• Production experience with LLM applications and agentic workflows.

Responsibilities

• Identify product problems where AI creates value and lead solutions from proof of concept to production.
• Select and adapt model architectures for CV and agentic AI use cases.
• Design experiments, evaluate model quality, and recommend investments.

Skills

Applied AI

AI leadership

MLOps

LLM applications

Communication

Tools

CI/CD

Containers

Monitoring

Job description

Role overview

Lead applied AI work across product teams, turning machine learning research into reliable features for complex, unstructured data. The role spans computer vision, large language models, agentic workflows, and multimodal learning, with responsibility from early problem definition through production deployment. You’ll work closely with product and engineering partners and draw on a research team for technical review.

Responsibilities

• Identify product problems where AI can create value, then scope and lead solutions from proof of concept to production.
• Select and adapt model architectures and training or fine‑tuning approaches for computer vision and agentic AI use cases.
• Design experiments, evaluate model quality, and recommend which approaches merit further investment.
• Make and explain trade‑offs among accuracy, interpretability, latency, and cost.
• Apply MLOps tooling and practices to deploy, monitor, and maintain production models.
• Share findings with research peers and keep the team current on useful methods and evaluation approaches.

Requirements

• 7–10 years of hands‑on applied AI or machine learning experience in industry, including systems shipped to solve real problems.
• Experience leading AI work independently, including taking a project from prototype to production without a dedicated ML engineering team.
• Practical MLOps experience, including model CI/CD, containers, deployment, and monitoring.
• Ability to work across product, engineering, and nontechnical groups and communicate technical decisions clearly.
• Production experience with LLM applications and agentic workflows, including retrieval, tool use, and evaluation.

Nice to have

• Experience with computer vision in areas such as autonomous vehicles, medical imaging, or industrial inspection.
• Familiarity with construction, civic technology, building, regulatory, or compliance work.
• Interest in responsible AI and comfort working in a lean, early‑stage environment.

Benefits and work setup

The role is remote, with occasional travel for team meetings, typically once or twice a year. The stated base salary range is CAD $150,000–$180,000, depending on skills and experience. Benefits and time off are offered, with details dependent on employment type.