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 Civ Check 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 Civ Check 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 team-oriented environment
Stay current on techniques, benchmarks, and tooling across computer vision, generative AI, NLP, and multimodal learning — and bring the practical 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 team Familiarity with diffusion models, model distillation, or multimodal architectures in production Deep, 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 performance Sharp experimental and statistical intuition; comfortable making decisions from messy, incomplete results and separating critical unknowns from nice-to-haves Strong proficiency in Python and experience with Py Torch,



Tensor Flow, JAX, or similar deep learning frameworks Hands‑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 problems Strong experience building agentic AI workflows and LLM‑powered applications in production, including retrieval, tool use, evaluation, and guardrails Excellent communication skills: you can align stakeholders, justify trade‑offs, write clear design proposals, and explain AI concepts to engineers, executives, and customers alike Strong software engineering skills, including Git, testing, API design, and modular code that integrates cleanly into existing products and that non‑ML engineers can maintain Hands‑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 stakeholders Significant experience with computer vision and image processing, including feature extraction, object detection, segmentation, and geometric transformations Interest in the ethical implications of AI technology and responsible AI development and design Experience in a forward‑deployed, embedded, or solutions engineering role, bringing AI into teams or products that didn’t have it before Preference for or comfort thriving in an early‑stage or startup environment Experience developing computer vision systems requiring high accuracy and reliability under strict tolerances — for example, in autonomous vehic

📌 Senior Applied Ai Engineer (Winnipeg)
🏢 Clariti
📍 Winnipeg