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Remote Machine Learning Jobs in Toronto, ON (NOW HIRING)

ML/AI Engineer

Toronto, ON · On-site +1

CA$110K - CA$150K/yr

The ML / AI Engineer design, build, deploy, and operate production-grade machine learning and ... The role will be remote. Why Join Levio? * Work on complex,high impactdigital transformation ...

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 ...

Data Platform Engineer Analyst

Maple, ON · On-site +1

CA$94K - CA$136K/yr

Working with renowned, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and ...

New

Data Platform Engineer Analyst

Unionville, ON · On-site +1

CA$94K - CA$136K/yr

Working with renowned, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and ...

New

Data Platform Engineer Analyst

Mississauga, ON · On-site +1

CA$94K - CA$136K/yr

Working with renowned, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and ...

New

Data Platform Engineer Analyst

Brampton, ON · On-site +1

CA$94K - CA$136K/yr

Working with renowned, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and ...

New

Data Platform Engineer Analyst

Toronto, ON · On-site +1

CA$94K - CA$136K/yr

Working with renowned, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and ...

... Machine Learning, or AI technologies. * Passion for contributing to open-source tools and communities. * Knowledge of advanced AWS services or emerging technologies. Why Work Here * Remote-First ...

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Showing results 1-20

Remote Machine Learning information

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in Toronto, ON? The most popular types of Machine Learning jobs in Toronto, ON are:
What are popular job titles related to Remote Machine Learning jobs in Toronto, ON? For Remote Machine Learning jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Toronto, ON look for? The top searched job categories for Remote Machine Learning jobs in Toronto, ON are:
Infographic showing various Remote Machine Learning job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Engineering Manager, Data Science (AdTech)

Engineering Manager, Data Science (AdTech)

Fluent, LLC

Toronto, ON • Remote

Full-time

Medical, Dental, Vision, Retirement

Re-posted 24 days ago


Job description

Fluent is building the next-generation advertising network, Partner Monetize & Advertiser Acquisition. Our vision is to build an ML/AI-first network of advertisers and publishers to achieve a common objective - elevating relevancy in E-commerce for everyday shoppers.

As our Engineering Manager, Data Science, you will lead the team responsible for driving business value through machine learning and advanced analytics in the Adtech space. You will own ROAS optimization, audience propensity modeling, and deep learning powered capabilities that differentiate Fluent's advertising products and drive client success. We are seeking expert-level knowledge of sequence modeling (Transformers/Attention) and generative approaches for user behavior, moving beyond legacy logistic regression to implement deep architectures that solve for data sparsity and long-term user value.

This role combines hands-on ML expertise with people leadership, requiring you to set technical direction for modeling initiatives while building and developing a high-performing data science team.

This role is fully remote in Ontario, Canada, with occasional travel to NYC.

What You'll Do

Machine Learning & Modeling

  • Drive the Deep Learning Evolution: Lead the architectural transition from legacy tree-based models (XGBoost) to advanced Neural Network architectures (Deep Learning) for audience propensity, lookalike modeling, and real-time segmentation.
  • Own Value-Based Bidding (ROAS): Evolve our bidding strategy from simple conversion prediction to sophisticated ROAS-based optimization, developing models that predict user value (LTV) to maximize client returns within dynamic auction environments.
  • Champion Agentic AI & Automation: Spearhead the exploration and adoption of autonomous agentic workflows to enhance decisioning and operational efficiency, moving beyond static models to self-correcting systems.
  • Build Production Deep Learning Systems: Oversee the end-to-end engineering of high-scale inference pipelines, including embedding layers, real-time feature stores, and low-latency serving infrastructure such as ONNX, TensorRT etc.
  • Advance MLOps & Experimentation: Establish rigorous MLOps practices for model versioning and drift detection while shifting further into multi-armed bandit strategies (Exploration vs. Exploitation) that optimize directly for business outcomes (Revenue/GP) rather than just model metrics.

Leadership & Collaboration

  • Lead and grow the Data Science team: hiring, mentoring, performance management, and career development.
  • Partner with Product and Client Success to translate business requirements into ML solutions and communicate model capabilities.
  • Coordinate with Data Platform team to ensure reliable data foundations and feature pipelines for modeling.
  • Translate complex ML concepts into actionable insights for business stakeholders and executives.
  • Set technical direction and foster a culture of innovation, rigor, and continuous improvement.

Requirements

  • PhD (preferred) or Master's Degree in Computer Science, Mathematics, or other Quantitative Field.
  • 8+ years of experience in Data Science or ML Engineering, with at least 2 years managing or leading technical teams.
  • AdTech Deep Learning Architecture Expertise: Deep hands-on experience with modern ranking and retrieval architectures (e.g., DLRM, DCNv2, Two-Tower), with a focus on multi-objective learning (MMoE) to jointly optimize for clicks, conversions, and revenue.
  • Strategic Ownership of Agentic AI: Demonstrated passion for and aptitude in defining the roadmap for autonomous agentic systems. You must be ready to learn, champion, and own the evolution from static RAG to production-grade agentic orchestration.
  • Real-Time Inference & Engineering: Experience deploying complex models into high-throughput, low-latency production environments (familiarity with ONNX, TensorRT, or feature stores).
  • Commercial & Business Acumen: Ability to translate improved model performance (AUC/LogLoss) into tangible business metrics (GP, RPM) and prioritize R&D efforts based on ROI and unit economics.
  • Strong Python skills with a focus on Deep Learning frameworks (PyTorch, TensorFlow) as well as traditional ML libraries (XGBoost, scikit-learn).
  • Proven people management skills: Experience hiring, mentoring, and developing high-performing data science talent.
  • Excellent communication skills for translating technical concepts to business stakeholders and executives.

Nice-to-Haves

  • Hands-on Agentic Framework Experience: Familiarity with graph-based orchestration such as LangGraph, multi-agent systems (CrewAI), or emerging standards like Model Context Protocol (MCP).
  • ROAS optimization and campaign performance modeling.
  • Databricks and MLflow experience.
  • Experience with audience/customer modeling: propensity, lookalike, segmentation, or recommender systems.

About Us

Fluent, Inc. (NASDAQ: FLNT) is a commerce media solutions provider connecting top-tier brands with highly engaged consumers. Leveraging diverse ad inventory, robust first-party data, and proprietary machine learning, Fluent unlocks additional revenue streams for partners and empowers advertisers to acquire their most valuable customers at scale. Founded in 2010, Fluent uses its deep expertise in performance marketing to drive monetization and increase engagement at key touchpoints across the customer journey. For more insights visit:https://www.fluentco.com/

Benefits

At Fluent, we like what we do, and we like who we do it with. Our team is a tight-knit crew of go-getters; we love to celebrate our successes! In addition, we offer a fully stocked kitchen, catered lunch, and our office manager keeps the calendar stocked with activity filled events. When we're not eating, working out, or planning parties, Fluent folks can be found participating in networking events, and bonding across teams during quarterly outings to baseball games, fancy dinners, and a variety of activities. And we have all the practical benefits, too...

  • Competitive compensation
  • Ample career and professional growth opportunities
  • New Headquarters with an open floor plan to drive collaboration
  • Health, dental, and vision insurance
  • Pre-tax savings plans and transit/parking programs
  • 401K with competitive employer match
  • Volunteer and philanthropic activities throughout the year
  • Educational and social events
  • The amazing opportunity to work for a high-flying performance marketing company!

Salary Range: $180,000 to $225,000 CAD base, + competitive bonus. The base salary range represents the low and high end of the Fluent salary range for this position. Actual salaries will vary depending on factors including but not limited to location, experience, and performance.

Candidates may be at risk of targeting by malicious actors seeking personal information. Fluent recruiters will only reach out via LinkedIn or email with an @fluentco.com domain. Any outreach by Fluent via other sources (e.g. text, other domains etc) should be ignored.

Fluent participates in the E-Verify Program. As a participating employer, Fluent, LLC will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. Fluent, LLC follows all federal regulations including those set forth by The Office of Special Counsel for Immigration-Related Unfair Employment Practices (OSC). The OSC enforces the anti-discrimination provision ( 274B) of the Immigration and Nationality Act (INA), 8 U.S.C. 1324b.