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Machine Learning Engineer

Job in London, Ontario, K5Z, Canada
Listing for: Grammarly
Full Time position
Listed on 2026-10-05
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 279000 - 361000 CAD Yearly CAD 279000.00 361000.00 YEAR
Job Description & How to Apply Below
Position: Machine Learning Engineer, Growth

Grammarly is excited to offer a remote‑first hybrid working model. Team members work primarily remotely in the United States, Canada, Ukraine, Germany, or Poland. Certain roles have specific location requirements to facilitate collaboration at a particular Grammarly hub.

All roles have an in‑person component:
Conditions permitting, teams meet 2–4 weeks every quarter at one of Grammarly’s hubs in San Francisco, Kyiv, New York, Vancouver, and Berlin, or in a workspace in Kraków. This flexible approach gives team members the best of both worlds – plenty of focus time along with in‑person collaboration that fosters trust and unlocks creativity.

Grammarly team members in this role must be based in the United States or Canada, and they must be able to collaborate in person 2 weeks per quarter, traveling if necessary to the hub(s) where the team is based.

Opportunity

Grammarly is the world’s leading AI writing assistance company trusted by over 30 million people and 70,000 professional teams every day. From instantly creating a first draft to perfecting every message, Grammarly’s product offerings help people at 96% of the Fortune 500 get their point across—and get results. Grammarly has been profitable for over a decade because we’ve stayed true to our values and built an enterprise‑grade product that’s secure, reliable, and helps people do their best work—without selling their data.

We’re proud to be one of Inc.’s best workplaces, a Glassdoor Best Place to Work, one of TIME’s 100 Most Influential Companies, and one of Fast Company’s Most Innovative Companies in AI.

To achieve our ambitious goals, we’re looking for a Machine Learning Engineer to join our Marketing Technology team. This team is responsible for building systems that empower and enhance the company’s marketing efforts and strategies. The person in this role will help shape marketing strategies, enhance customer experiences, and optimize marketing campaigns. They will be responsible for leveraging data and advanced algorithms to improve the performance and efficiency of advertising campaigns with the goal of maximizing the return on investment (ROI) for ad spend and delivering targeted ads to the right audience.

Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

Your impact

As a Lead Machine Learning Engineer of the Growth org, you will transform the way ML is applied to solve Growth problems. Your work will directly impact the topline KPIs that Growth team contributes to the overall business. You will lead research, exploration and help establish a robust ML development process for the organization. This is a high‑impact role with a direct line of the channel with the area leads and the senior leadership team.

  • Drive business impact by building scalable end‑to‑end machine learning solutions for challenging marketing problems.
  • Help Growth EPD and Marketing teams make data‑driven decisions.
  • Your work will help drive multiple topline KPIs - LTV/CAC, number of activated and retained users, bookings revenue, etc.
  • Promote excellence and best practices across the machine learning team in research, implementation, tooling, and system design.
  • Work cross‑functionally with various teams:
    Marketing, Marketing Analytics, Data Science, ML Infrastructure, and Product, to name a few.
  • Effectively communicate technical machine learning results in a business context where most people are not machine learning experts.
Qualifications
  • Embodies our EAGER values – ethical, adaptable, gritty, empathetic,…
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