The job ad is older than 1 month and may no longer exist.
Grammarly is excited to offer a remote-first hybrid working model. Team members can work primarily remotely in the United States, Canada, Ukraine, Germany, Poland, and Portugal. Conditions permitting, teams will meet in person a few weeks every quarter at one of Grammarly's hubs, currently in San Francisco, Kyiv, New York, Vancouver, and Berlin, or in a shared workspace in Krakow.
Grammarly team members in this role must be based in Canada or the United States.
Grammarly empowers people to thrive and connect, whenever and wherever they communicate. More than 30 million people and 30,000 teams around the world use our AI-powered writing assistant every day. All of this begins with our team collaborating in a values-driven and learning-oriented environment.
To achieve our ambitious goals, we’re looking for a Software Engineer focused on machine learning to join our team. This individual will be responsible for building end-to-end intelligence systems that solve complex user problems, including applying ML to solve new problems as well as building the infrastructure and systems that will enable this to operate effectively at scale. The role will have the opportunity to provide feedback about the systems and tools in place to facilitate the creation and improvement of a machine learning platform that can increase the efficacy of the engineering team.
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. Read more about our stack or hear from our team on our technical blog.
The Software Engineer for machine learning will need to stay up-to-date on the quickly evolving field of NLP while also focusing on building production systems. The majority of the problems we’re tackling haven't already been solved elsewhere, which provides the opportunity for creativity and innovative problem-solving.
Working on the Machine Learning team requires close partnership with analytical linguists, computational linguists, and research scientists. You will have the chance to deepen your skills in machine learning and deep learning while increasing breadth in related areas to up-level our entire team.
In this role, you will:
We’re looking for someone who
Support for you, professionally and personally
We encourage you to apply
At Grammarly, we value our differences, and we encourage all—especially those whose identities are traditionally underrepresented in tech organizations—to apply. We do not discriminate on the basis of ancestry, race, place of origin, political belief, religion, marital status, family status, physical or mental disability, sex, sexual orientation, gender identity or expression, age, or any other characteristic protected by law. Grammarly is an equal opportunity employer and abides by the Employment Equity Act.
Grammarly currently supports the long-term work of team members in the following Canadian provinces: British Columbia, Ontario
Grammarly currently supports the long-term work of team members in the following US states: Arizona, California, Colorado, Florida, Georgia, Illinois, Maine, Massachusetts, Minnesota, Nevada, New Jersey, New York, North Carolina, Oregon, Pennsylvania (Kennett Township, New London Township, Pittsburgh City, Shaler Township), South Carolina, Texas, Utah, Virginia, and Washington, as well as the District of Columbia
Please note that Grammarly’s COVID-19 vaccination policy requires that all team members in North America be vaccinated against COVID-19 to meet in person for Grammarly business or to work from a North America hub location. It is expected that this will be a requirement for this role. Qualified candidates in North America who cannot be vaccinated for medical reasons or because of a sincerely held religious belief may request a reasonable accommodation to this policy. For Europe, this policy requires team members to be vaccinated or produce a daily negative COVID-19 test administered on-site to work from the hub or attend in-person meetings.