Grammarly offers a remote-first hybrid working model. Team members can work primarily remotely. Teams will meet in person every quarter in one of Grammarly’s hubs, currently in San Francisco, Vancouver, New York, and Kyiv. To ensure that teams are able to overlap in their working hours and to meet face-to-face when needed, all team members need to live within three time zones of their direct team.
Grammarly team members who will be collaborating at our Vancouver hub must be based in Canada.
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:
- Build end-to-end machine learning solutions to solve complex customer problems.
- Collaborate with applied researchers to ensure they are well-calibrated on the constraints of the production system, ensuring their research proceeds along practical pathways as they explore novel techniques to tackle previously unsolved problems.
- Effectively communicate technical machine learning results in a business context where most people are not machine learning experts.
- Build the systems to help applied researchers scale their models in a production environment.
- Design experiments, including for offline prototypes in a statistically sound way that will provide actionable data and enable us to make reliable decisions as we iterate on a project.
- Promote excellence and best practices across the machine learning team in regards to research, implementation, tooling, and system design.
- Work cross-functionally across multiple partner teams to get new features shipped across our many interfaces.
We’re looking for someone who
- Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
- Understands traditional machine learning algorithms and how to use them effectively in practice.
- Is familiar with deep learning and its applications in industry.
- Has a strong working knowledge of statistics as it relates to sampling methodologies and designing experiments
- Understands data structures and algorithms at a level sufficient to write performant code when working with large datasets or large incoming data streams.
- Is aware of NLP techniques to effectively work with very high-dimensional, sparse data.
- Has enough experience with academic research to be comfortable reading and implementing papers to reproduce their results.
Support for you, professionally and personally
- Professional growth: We hire people we trust, and we give team members autonomy to do their best work. We also support professional development with training, coaching, and regular feedback.
- A connected team: Grammarly builds products that help people connect, and we apply this mindset to our own team. We have a highly collaborative culture supported by our EAGER values. We also take time to celebrate our colleagues and accomplishments with global, local, and team-specific events and programs.
- Comprehensive benefits: Grammarly offers all team members competitive pay along with a benefits package encompassing superior health care (including mental health benefits). We also offer support to set up a home office, ample and defined time off, gym and recreation stipends, and more.
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.
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 Ukraine, this policy requires team members to be vaccinated or produce a daily negative COVID-19 test administered at the Kyiv hub to work from the hub or attend in-person meetings.