Senior Applied AI Engineer

Clariti; Canada; On-site; CAD 120,000 - 190,000; Full time

Benefits offered by this job

Flexible Work Culture

Professional Development

Team Building Events/Outings

Motivated Team

Corporate Bonus Plan

Job summary

Clariti seeks a Senior Applied AI Engineer to serve as a forward-deployed AI expert across product teams. You’ll translate the latest ML research into practical, production-ready features, spanning LLMs, agentic AI workflows, computer vision, and multimodal learning.

You’ll report into CivCheck AI Research, but work day-to-day embedded with product and engineering managers across the company, owning end-to-end delivery and shaping AI direction in a lean, fast-moving environment.

Qualifications

• Led AI projects from concept to production in industry.
• Experience with diffusion models, multimodal architectures or similar.
• Hands-on training and fine-tuning of models with modern frameworks.

Responsibilities

• Own AI problems end-to-end from scoping to production.
• Embed with product teams and collaborate with engineers.
• Design, run and evaluate experiments to drive impact.
• Shape technical direction with pragmatic trade-offs.

Skills

Applied AI

LLMs

MLOps

Python

PyTorch

Computer Vision

Agentic AI

Cross-functional

Experimentation

Cloud platforms

Tools

AWS

Docker

Kubernetes

CI/CD

Job description

• We’re seeking a Senior Applied AI Engineer to serve as a forward-deployed AI expert across Clariti’s product teams
• You’ll turn the latest machine learning research into practical, production-ready features, spanning large language models (LLMs), agentic AI workflows, computer vision, and multimodal learning
• You’ll report into our CivCheck AI Research team, the home of Clariti’s AI expertise, but your day-to-day work will be embedded with product and engineering managers across the company
• On these projects, you’ll often be the AI specialist, bringing expertise in model selection, deployment, and agentic AI to bring brand-new capabilities in an AI-native transformation of Clariti’s existing products
• That means you’ll drive projects end to end: scoping the problem, building the proof of concept, and taking it all the way to production with our MLOps tooling and infrastructure
• You’ll bring your proposed approaches to the CivCheck AI Research team for design feedback, giving you a strong peer group for technical rigor while you own delivery within your product team
• The ideal candidate has spent years doing applied AI work in industry, is comfortable being the go-to AI person on a cross-functional team, and is energized by hard, open-ended problems in a lean, fast-moving environment
• Own computer vision and agentic AI problem domains, selecting and adapting architectures and training/fine-tuning strategies for the best results on complex, unstructured real-world data
• Drive the design and execution of experiments end to end, from framing the question to evaluating model performance and deciding what’s worth pursuing
• Help shape technical direction by identifying high-impact opportunities to improve our AI systems, drawing on applied experience and practical judgment
• Make pragmatic trade‑off calls across model accuracy, interpretability, latency, and cost, and directly own decisions in communication with stakeholders
• Share your experience with research teammates and help raise the bar for experimental rigor in a collaborative environment
• Stay current on techniques, benchmarks, and tooling across computer vision, generative AI, NLP, and multimodal learning — and bring the useful ones into practice
• Embed with product teams across Clariti, partnering with product and engineering managers to identify where AI can create the most value for our customers

Benefits

• Flexible Work Culture
• Professional Development
• Team Building Events/Outings
• Motivated Team
• Corporate Bonus Plan

Demonstrated experience as the lead or sole AI expert on a project, taking your own work from proof of concept through to production without relying on a dedicated ML engineering teamFamiliarity with diffusion models, model distillation, or multimodal architectures in productionDeep, demonstrated experience training and fine-tuning models using modern frameworks, including defining architectures, curating and cleaning datasets, tuning training parameters, and diagnosing training and validation performanceSharp experimental and statistical intuition; comfortable making decisions from messy, incomplete results and separating critical unknowns from nice-to-havesStrong proficiency in Python and experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworksHands‑on fluency with MLOps practices and infrastructure, including CI/CD for models, containerization, deployment, and monitoring7–10 years of hands‑on experience in applied AI/ML in industry, with a track record of shipping models and systems that solved real business problemsStrong experience building agentic AI workflows and LLM‑powered applications in production, including retrieval, tool use, evaluation, and guardrailsExcellent communication skills: you can align stakeholders, justify trade‑offs, write clear design proposals, and explain AI concepts to engineers, executives, and customers alikeStrong software engineering skills, including Git, testing, API design, and modular code that integrates cleanly into existing products and that non‑ML engineers can maintainHands‑on experience with end‑to‑end ML workflows on cloud platforms such as AWS, Azure, or GCPA proven ability to operate independently inside cross‑functional teams, working closely with product managers, engineering managers, and nontechnical stakeholdersSignificant experience with computer vision and image processing, including feature extraction, object detection, segmentation, and geometric transformationsInterest in the ethical implications of AI technology and responsible AI development and designExperience in a forward‑deployed, embedded, or solutions engineering role, bringing AI into teams or products that didn’t have it beforePreference for or comfort thriving in an early‑stage or startup environmentExperience developing computer vision systems requiring high accuracy and reliability under strict tolerances — for example, in autonomous vehicles, medical imaging, or industrial inspectionExposure to the construction, building, civic‑tech, or regulatory/compliance domains