Grammarly is excited to offer a remote-first hybrid working model, which combines the flexibility of working from home with the benefits of gathering in person. 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 times 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 who will be collaborating in Berlin must be based in Germany, Poland, or Portugal.

The opportunity 

Grammarly empowers people to thrive and connect, whenever and wherever they communicate. Every day, over 30 million people and 50,000 teams around the world rely on our AI-powered communication assistance technology. 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 Lead ML Platform Engineer to join our ML Infra team. Our AI-powered writing assistant leverages the latest NLP and DL technologies for state-of-the-art Grammatical Error Correction and advanced semantic features to help our users communicate clearly and confidently.

This role will be the technical and thought leader of a nimble and growing team that builds ML Platform, a set of technologies allowing our ML engineers, applied researcher scientists, and computational linguists to productively focus on their specialized expertise and spend less time on orchestration and infrastructure. This platform will accelerate the development of flagship Premium features that help users improve their communication.

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.

Your impact

As Lead ML Platform Engineer, you will:

  • Architect and build a machine learning platform to accelerate the development of ML solutions across the company and serve multiple constituents and stakeholders: ML engineers, applied research scientists, computational linguists, and data scientists who build user-facing features that rely on machine learning.
  • Research existing open-source tools and MLOps and Platform approaches taken by other companies to ensure we are building best-in-class technology while leveraging available components.
  • Guide the organization through buy vs. build trade-offs.
  • Drive toward material reduction in time spent by internal stakeholders on infrastructure work developing and expanding new features and capabilities while coordinating across many teams using ML to ensure their core needs are addressed, minimal time is spent on migrations, and the platform increases productivity.
  • Scale our ability to reuse models, features, and code in ML systems across the company.
  • Produce system architectures and designs that balance the needs of multiple constituencies and make core scenarios seamless.
  • Enable researchers 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 as well as modern deep learning approaches.
  • Is aware of unique challenges with sparse feature sets and the Transformer-based pre-trained deep learning models central to NLP.
  • 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.
  • Has a consistent record working with internal partners (data platform, analytics, and data science teams) and strategic stakeholders (product managers and security teams).
  • Stays up-to-date in the fast-moving field of ML, DL, NLP, and MLOps.
  • Is aware of existing ML cloud platforms and tools and of the excellent platforms others are using, such as Michelangelo or FBLearner Flow.

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, admission discounts, and more.

We encourage you to apply

At Grammarly, we value our differences, and we encourage all to apply. Grammarly is an equal opportunity company. We do not discriminate on the basis of race or ethnic origin, religion or belief, gender, disability, sexual identity, or age.

For more details about the personal data Grammarly collects during the recruitment process, for what purposes, and how you can address your rights, please see the Grammarly Data Privacy Notice for Candidates here.

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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