Machine Learning Engineer, Mobile

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 Poland or Germany and 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.

We are seeking a skilled Machine Learning Engineer to join our Mobile team and help us achieve our ambitious goals. As the first Machine Learning Engineer on our Mobile Team, this person will be instrumental in developing and deploying AI technologies directly to user devices, enhancing their communication experience across mobile platforms. Our Machine Learning Engineer’s contributions will directly enhance features that improve everyday communication for millions of users and give you a voice in influencing the Mobile Product Roadmap.

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. You can hear more from our team on our technical blog.

Your impact

As a Machine Learning Engineer on our Mobile Team, you will:

• Design, develop, and optimize machine learning models that operate efficiently on mobile devices at scale.
• Collaborate with mobile developers to integrate ML technologies seamlessly into Grammarly’s iOS and Android applications.
• Own improving the NLP algorithms that power the iOS keyboard, including autocorrect, key prediction, autocomplete, and swipe typing.
• Launch and monitor the deployment of ML models via A/B testing and diagnose and respond to issues that arise with models in the field.
• Lead cross-functional initiatives, collaborating closely with teams to bring new machine-learning-driven features from concept to deployment.
• Effectively communicate technical machine learning results in a business context where most people are not machine learning experts, ensuring team clarity and alignment.
• Leverage the latest academic research to develop cutting-edge solutions, advancing Grammarly’s leadership in AI-enhanced communication tools.

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.
• Has 8 years of overall software development experience and 4 years in machine learning, with a strong focus on natural language processing and on-device machine learning.
• Is proficient in multiple dev environments like Python and C++.
• Has experience in development for Mobile iOS or Android platforms.
• Understands data structures and algorithms at a level sufficient to write performant code when working with large datasets or incoming data streams.
• Has enough experience with academic research to collaborate with researchers and be comfortable reading and impleme