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Remote Machine Learning Quant Jobs in Toronto, ON

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks. * Review model-generated implementations involving model ...

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Qualifications: - MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... quantitative background and coursework in or working knowledge of linear algebra, calculus, and ...

D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field. * 7 -10+ years of experience in data science or advanced analytics, with ...

D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field. * 7 -10+ years of experience in data science or advanced analytics, with ...

D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field. * 7 -10+ years of experience in data science or advanced analytics, with ...

Follow advancements in data science, machine learning, and healthcare analytics Qualifications ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

ML Research Scientist - PhD

Toronto, ON · Remote

CA$110 - CA$145/hr

Remote Role Responsibilities * Evaluate the accuracy and depth of AI-generated content to strengthen reasoning and rigor in model outputs . * Review complex machine learning research for alignment ...

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

Remote Role Responsibilities * Construct enterprise data science scenarios for large-scale ... Build analytics tasks across machine learning model development , enterprise data pipelines , and ...

D. in a quantitative field such as computer science, applied mathematics, statistics or machine learning - or an equivalent combination of education and experience. You're likely to be a MSFT ...

Showing results 21-40

Remote Machine Learning Quant information

What is the difference between Remote Machine Learning Quant vs Remote Data Scientist?

AspectRemote Machine Learning QuantRemote Data Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or financeDegrees in data science, statistics, or related fields; certifications like CAP or DASCA
Work EnvironmentFinancial firms, hedge funds, or quantitative trading companiesTech companies, research institutions, or consulting firms
Industry UsageFinance, trading, hedge fundsTechnology, healthcare, marketing, finance
Common Search/ComparisonYesNo

Remote Machine Learning Quants focus on developing quantitative models for trading and investment strategies within financial firms, often requiring finance-specific knowledge. Remote Data Scientists work across various industries, applying data analysis and machine learning to solve diverse business problems. While both roles involve machine learning, Quants are more finance-oriented, whereas Data Scientists have broader industry applications.

ML Engineer - AI Coding Expert

Mercor

Toronto, ON • Remote

CA$85/hr

Full-time

Posted 9 days ago


Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: ML Engineer (Coding Agent Experience)
Type: Contract
Compensation: $85/hour
Location: Remote

Role Responsibilities

  • Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
  • Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
  • Identify bugs, edge cases, performance issues, and failure modes.
  • Compare outputs from multiple frontier models and assess their strengths and weaknesses.
  • Apply professional engineering judgment to realistic ML engineering scenarios.

Qualifications

Must-Have

  • 2+ years of professional machine learning engineering experience.
  • Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
  • Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  • Ability to evaluate model-generated machine learning implementations and technical tradeoffs.

Preferred

  • Experience deploying ML systems to production.

Compensation & Legal

  • $400 per accepted task
  • Compensation is tied to accepted work.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.