We're hiring a Machine Learning Engineer to join our core ML team in Toronto. You'll design, train, and deploy the models that power Tofu's fraud detection, deepfake analysis, and identity verification systems — directly shaping the accuracy and reliability of the product at scale.

What You'll Do

Design, train, and ship ML models for fraud detection, synthetic identity classification, and deepfake (audio, image, video) detection.
Build and maintain robust evaluation pipelines, including labeled datasets, benchmarks, and continuous monitoring for model drift.
Productionize models in collaboration with backend engineers — owning latency, throughput, and reliability requirements end-to-end.
Research and prototype novel approaches to adversarial fraud, including multi-modal signal fusion and active-learning loops.
Partner with product and threat intelligence to translate emerging fraud patterns into trainable signals.

What You'll Bring

A bias toward shipping — comfortable balancing research rigor with pragmatic delivery in a fast-paced environment.
Strong analytical and problem-solving skills, with deep curiosity about adversarial systems.
Excellent communication and the ability to explain trade-offs and model behavior to non-ML stakeholders.
A collaborative mindset and willingness to mentor more junior engineers and researchers.
Strong technical documentation skills.

Required Experience

Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field (Master's or PhD a plus).
5+ years of professional experience building and deploying ML systems in production.
Expert proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX).
Hands-on experience with at least one of: computer vision, audio/speech models, NLP, or anomaly detection.
Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Docker and Kubernetes.
Strong SQL and data wrangling skills.
Experience with vector databases, embeddings, and large-scale retrieval (Elasticsearch, FAISS, pgvector).

Preferred Experience

Experience with deepfake detection, biometrics, or generative model forensics.
Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, SageMaker).
Experience in fraud, trust & safety, or security-adjacent domains.
Familiarity with adversarial ML and red-teaming techniques.

Why Tofu and this Role

You'll help build the trust layer for the internet — one of the defining problems of the AI era.
You'll join a team obsessed with building a generational company.
Early engineers have real ownership, real impact, and unlimited growth.

Benefits & Perks