Machine Learning Engineer, Detection (TOR)

Doppel
Toronto
Workplace: HybridFull timeCAD 183,000 - 429,390 annuallyFunction: Data Science & Machine LearningSkills: ["Collaboration","Communication","Problem-solving"]

Design, train, and deploy models for batch and real-time inference to identify malicious or infringing content across diverse data sources. Collaborate with Detection and Infrastructure teams to ensure ML systems scale with web data, exploring NLP, embeddings, similarity search, and anomaly detection while translating real-world threats into production ML solutions.

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FursaFursa
Doppel
Doppel
4 months ago

Machine Learning Engineer, Detection (TOR)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Design, train, and deploy models for batch and real-time inference to identify malicious or infringing content across diverse data sources. Collaborate with Detection and Infrastructure teams to ensure ML systems scale with web data, exploring NLP, embeddings, similarity search, and anomaly detection while translating real-world threats into production ML solutions.
Location: Toronto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, train, and deploy models for both batch and real-time inference that identify malicious or infringing content across diverse data sources.
  • •Partner closely with the Detection and Infrastructure teams to ensure our ML systems scale with the volume of web data we ingest
  • •Work on problems that range from NLP and embeddings to similarity search, classification, and anomaly detection
  • •Collaborate directly with customers and internal stakeholders to translate real-world threats into production ML systems
  • •(Optional) Contribute to model monitoring and iteration to maintain performance in production environments

Pay and Benefits

Salary: CAD 183,000 - 429,390 annually
Equity and Bonus:Equity
Perks:Paid LeaveMeal AllowanceOffsites

Key Requirements

  • •Have experience building and deploying ML systems in production environments.
  • •Are comfortable working with large-scale datasets and distributed data processing frameworks.
  • •Understand the trade-offs between research-quality models and production-ready systems.
  • •Are excited about solving real-world problems where the adversary is constantly evolving.
  • •Design, train, and deploy models for both batch and real-time inference that identify malicious or infringing content across diverse data sources.
Experience:CybersecuritySaaS
Skills:CollaborationCommunicationProblem-solving
Tech Stack:NLPEmbeddingsSimilarity searchAnomaly detection

Company Brief

Doppel
Doppel is an AI-native social engineering defense platform that detects, disrupts, and dismantles impersonation, phishing, and digital risk infrastructure for brands, executives, and employees using AI agents plus human analysis.
Industry: Cybersecurity
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: USD 500M to 1B
Funding: Series C
Headquarters: Covina, United States
Founded: 2022
Glassdoor
Glassdoor: 4.6
WebsiteLinkedInGlassdoor