Machine Learning Engineer (Mobile Team)

Grammarly

Grammarly

Software Engineering
Remote
Posted on Thursday, October 13, 2022

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.

The opportunity

Every day, tens of millions of people and 50,000 professional teams worldwide trust Grammarly's AI and human expertise to help ideate, compose, revise, and comprehend communications. Our team members have the autonomy to take on exciting challenges in pursuit of our mission to improve lives by improving communication. Together, we're building on more than a decade of steady growth and profitability. We're defining the communication assistance category for individuals, enterprises, and developers with tailored service offerings: Grammarly Free, Grammarly Premium, Grammarly Business, and Grammarly for Education. Our latest product offering, GrammarlyGO, brings the power of generative AI to our users. It all begins with our team collaborating in an inclusive, values-driven, and learning-oriented environment.

To achieve our ambitious goals, we’re looking for a Machine Learning Engineer to join our Mobile Machine Learning team. This person will help build a more private and reliable version of Grammarly that is fully offline and can function exclusively on a user’s device—whether it’s a phone, tablet, laptop, or browser. They will have the opportunity to explore every part of Grammarly’s system and understand all of its components, from the classic NLP pipelines with parsers and text classifiers, to the cutting-edge deep learning models that now power the Grammarly system.

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 a Machine Learning Engineer on the Mobile team, you will play a critical role in developing new and innovative AI-based features for Grammarly’s mobile offerings, improving our foundational keyboard quality, and ensuring that Grammarly’s functionality is available offline and can work without internet connectivity. Our team works with many other teams across the company to directly develop features, improve existing models, and provide enabling on-device infrastructure. This allows us help the whole company address the unique challenges and opportunities of building on-device ML-based features. We believe these approaches allow us to improve users’ privacy without harming the high level of quality and experience that we provide.

In this role, you will:

  • Adapt existing cloud-based models to different user environments (mobile, desktop, etc.).
  • Improve the quality of our core keyboard input by developing existing models that we’ve built within the team (autocorrect, swipe, and phrase-completion models) on Android and iOS.
  • Prototype and implement new mobile Grammarly features that take advantage of LLMs and generative AI advancements.
  • Support and improve our cloud infrastructure for on-device models, A/B testing, and distribution.
  • Develop more sophisticated on-device ML inference capabilities to enable new offline or client-only user experience as well as migrate server-side functionality to the client. This would enable new functionality, preserve and enhance user privacy and reduce server costs.

We’re looking for someone who

  • Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
  • Is able to collaborate in person 2 weeks per quarter, traveling if necessary to the hub where the team is based.
  • Is a strong coder, with a good understanding of algorithms and data structures.
  • Has experience with native development (most of our code is in C++).
  • Has experience developing machine learning models.
  • Has experience with natural language processing or model distillation.

Support for you, professionally and personally

  • Professional growth: We believe that autonomy and trust are key to empowering our team members to do their best, most innovative work in a way that aligns with their interests, talents, and well-being. We support professional development and advancement 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. Our remote-first hybrid model enables a highly collaborative culture supported by our EAGER (ethical, adaptable, gritty, empathetic, and remarkable) values. We work to foster belonging among team members in a variety of ways. This includes our employee resource groups, Grammarly Circles, which promote connection among those with shared identities, such as BIPOC and LGBTQIA+ team members, women, and parents. We also celebrate our colleagues and accomplishments with global, local, and team-specific programs.

Compensation and benefits

Grammarly offers all team members competitive pay along with a benefits package encompassing the following and more:

  • Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
  • Disability and life insurance options
  • 401(k) and RRSP matching
  • Paid parental leave
  • Twenty days of paid time off per year, eleven days of paid holidays per year, and unlimited sick days
  • Home office stipends
  • Caregiver and pet care stipends
  • Wellness stipends
  • Admission discounts
  • Learning and development opportunities

Grammarly takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US and Canada locations are categorized into compensation zones based on each geographic region’s cost of labor index. For more information about our compensation zones and locations where we currently support employment, please refer to this page. If a location of interest is not listed, please speak with a recruiter for additional information.

Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.

United States:
Zone 1: $271,000 - $370,000/year (USD)
Zone 2: $244,000 – $333,000/year (USD)
Zone 3: $230,000 – $315,000/year (USD)
Zone 4: $217,000 – $296,000/year (USD)
Canada:
Zone 1: 224,000 – 330,000/year (CAD)
Zone 2: 190,000 – 281,000year (CAD)

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 race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Grammarly is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).

Please note that EEOC is optional and specific to US-based candidates.

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All team members meeting in person for official Grammarly business or working from a hub location are strongly encouraged to be vaccinated against COVID-19.

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