Software Engineer, Machine Learning Platform

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Machine Learning and Research ∙ Remote - Canada

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.

The opportunity

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 platforms to join our team. This individual will be responsible for building a platform to power machine learning systems across the company. The platform will be used by engineers, scientists, linguists, and others, enabling experts to spend more time using their machine learning expertise and less time on infrastructure-related work to support it.

Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs. The system you build will play an important role in accelerating these results. Read more about our stack or hear from our team on our technical blog.

Your impact

The Software Engineer focusing on machine learning platforms will need to stay up-to-date in this fast-moving field. This includes being aware of cloud platforms and open source tools that can be used in such a platform—and ideally being aware of some of the excellent platforms others are using, such as Michelangelo or FBLearner Flow. Natural language processing technology is critical to Grammarly’s success, so the platform will need to handle unique challenges, including enormous, sparse feature sets and the latest Transformer-based pre-trained deep learning models.

In this role, you will:

  • Build a machine learning platform to accelerate the development of ML solutions across the company.
  • Work with a wide range of internal customers, including computational linguists, machine learning engineers, and research scientists.
  • Collaborate with people building user-facing features that rely on machine learning to understand the challenges and bottlenecks in the process.
  • Produce system architectures and designs that balance the needs of multiple constituencies and make core scenarios seamless.
  • Enable researchers to translate models they create into systems operating at scale.
  • Help make Grammarly’s diverse array of machine learning systems more maintainable by providing a common set of infrastructure, orchestration, and monitoring.

We’re looking for someone who

  • Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
  • Is able to collaborate in person 2–4 weeks per quarter, traveling if necessary to the hub where the team is based.
  • Understands traditional machine learning algorithms and modern deep learning approaches as well.
  • Understands data structures and algorithms at a level sufficient to write performant code when working with large datasets or large incoming data streams.
  • Has experience with system design and building internal tools.
  • Is aware of NLP techniques to effectively work with very high-dimensional, sparse data.

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 a product that helps 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.

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

 

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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.

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