Machine Learning Engineer, Responsible AI



Software Engineering, Data Science
Posted on Thursday, October 26, 2023

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

Grammarly is the world’s leading AI writing assistance company trusted by over 30 million people and 70,000 professional teams every day. From instantly creating a first draft to perfecting every message, Grammarly’s product offerings help people at 96% of the Fortune 500 get their point across—and get results. Grammarly has been profitable for over a decade because we’ve stayed true to our values and built an enterprise-grade product that’s secure, reliable, and helps people do their best work—without selling their data. We’re proud to be one of Inc.’s best workplaces, a Glassdoor Best Place to Work, one of TIME’s 100 Most Influential Companies, and one of Fast Company’s Most Innovative Companies in AI.

To achieve our ambitious goals, we’re looking for a Machine Learning Engineer specializing in NLP to join our Responsible AI team. The Responsible AI team develops technology integrated into all Grammarly products to make them as safe and fair as possible. The person in this role will be responsible for developing and implementing new ML solutions to improve the safety and fairness of various Grammarly products.

We work in small, cross-functional project teams to leverage state-of-the-art ML advances, deep linguistic expertise, and human-centered product design. The person in this role will apply ML to solve new and challenging problems and build the infrastructure and systems to operate solutions effectively at scale. This will involve working on a highly cross-functional team in close partnership with Analytical Linguists, Computational Linguists, Data Scientists, and more.

Grammarly’s ML practitioners have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. They will have the chance to broaden and deepen their machine learning and deep learning skills. Read more about our stack or hear from our team on our technical blog.

Your impact

As a Machine Learning Engineer on the Responsible AI team, you will significantly impact Grammarly and its users by building technology that improves safety and fairness for every single product Grammarly launches. Most of the problems we’re tackling haven’t been solved elsewhere, which provides the opportunity for creative and innovative problem-solving.

In this role, you will:

  • Build scalable end-to-end machine learning solutions for challenging customer problems.
  • Explore novel techniques to tackle previously unsolved problems.
  • Promote excellence and best practices across the machine learning team in research, implementation, tooling, and system design. Mentor other team members in these areas.
  • Work cross-functionally with various teams to integrate risk mitigation technology into different Grammarly products.
  • Effectively communicate technical machine learning results in a business context where most people are not machine learning experts.

We’re looking for someone who

  • Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
  • Is inspired by our MOVE principles, which are the blueprint for how things get done at Grammarly: move fast and learn faster, obsess about creating customer value, value impact over activity, and embrace healthy disagreement rooted in trust.
  • Is able to collaborate in person 2 weeks per quarter, traveling if necessary to the hub where the team is based.
  • Understands traditional machine learning algorithms, state-of-the-art techniques—including deep learning—and how to use them effectively in practice.
  • Has expertise in NLP, safety, fairness, and Responsible AI.
  • Is comfortable reading academic papers and can take interesting ideas and apply them.
  • Understands data structures and algorithms at a level sufficient to write performant code when working with large datasets or large incoming data streams.

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 – $337,000 (USD)
Zone 2: $244,000 – $303,000 (USD)
Zone 3: $$230,000 – $286,000(USD)
Zone 4: $217,000 – $270,000 (USD)
Zone 1: $224,000 – $279,000 (CAD)
Zone 2: $190,000 – $237,000 (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.




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.