Orgn Technologies is building infrastructure for the physical collectibles market, starting with high-value trading cards, sports cards, comics, and related collector assets. Our goal is to create a trusted platform where collectors can discover, verify, manage, and safely trade physical collectibles online.We are early-stage, funded, and building toward our MVP. The engineering team is small, hands‑on, and focused on shipping reliable systems from first principles. We are looking for a Machine Learning Engineer who can help build AI/ML systems for provenance, ownership verification, item intelligence, fraud detection, search, and marketplace trust.This is a practical engineering role. You will work close to product and backend engineering, turning ambiguous marketplace and verification problems into production systems.Work Model: In office/hybrid. The initial phase is expected to be mostly in office for fast team building and product execution, with hybrid flexibility as the team scales.Employment Type: Full-time, permanentPay: CA$95,000.00-CA$135,000.00 per year + Stock OptionsWhat You’ll DoDesign, build, and deploy ML systems that support collectible verification, provenance signals, item matching, search, recommendations, trust, and fraud detectionWork with structured and unstructured data, including item metadata, images, text descriptions, transaction signals, and marketplace activityBuild evaluation pipelines for model quality, confidence scoring, false positives, false negatives, and human review workflowsPrototype and productionize computer vision, LLM, embedding, classification, ranking, or anomaly detection systems where appropriateCollaborate with backend engineers working in Node.Js and TypeScript to integrate ML services into the productCreate reliable APIs, data pipelines, monitoring,



and feedback loops for ML-powered product featuresHelp define what should be automated, what should stay human-reviewed, and how confidence should be represented to usersDocument assumptions, model limitations, risks, and tradeoffs clearlyWhat We’re Looking ForExperience building ML or AI systems that solve real product or operational problemsStrong Python skills and familiarity with ML libraries such as PyTorch, TensorFlow, scikit-learn, pandas, OpenCV, or similarAbility to evaluate model performance beyond simple accuracy, including edge cases, error analysis, and production failure modesExperience working with APIs, cloud services, databases, queues, or backend systemsComfort operating in an early-stage startup where requirements are evolving and ownership is highClear communication, pragmatic technical judgment, and the ability to explain tradeoffs to technical and non-technical teammatesNice to HaveExperience with computer vision, image similarity, embeddings, vector databases, LLMs, RAG, or multimodal modelsExperience with marketplace, fraud, trust and safety, collectibles, authentication, logistics, fintech, or high-value asset platformsFamiliarity with MLOps tools such as MLflow, Weights & Biases, Airflow, or similarExperience with TypeScript, Node.Js, React, or Next.JsInterest in trading cards, sports cards, TCGs, comics, or collector communitiesHow to ApplyPlease apply with your resume and links to relevant projects, technical writing, GitHub, portfolio work, or examples of shipped ML systems.Do not include passwords, API keys, government ID numbers, banking details, SIN, copies of permits, or other sensitive credentials in your application. Any legally required onboarding documents will only be requested after the appropriate hiring stage through secure channels.Orgn Technologies Inc. is an equal opportunity employer. We evaluate candidates based on relevant skills, experience, judgment, and ability to contribute to the role.#J-18808-Ljbffr

📌 Machine Learning Engineer - C$95,000 - C$135,000 A Year (Winnipeg)
🏢 ORGN Technologies
📍 Winnipeg