Engineering Manager, Machine Learning

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 in this role are required to live within a daily commutable distance to San Francisco. Grammarly may provide relocation assistance.
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 an Engineering Manager to join our Machine Learning team. This manager will lead and grow the ML Engineering team to build and support novel intelligence features with researchers and product managers. This team has an opportunity to shape the way Grammarly's Engineering team delivers ML features across the entire product. This role will be instrumental in helping to build ML-powered functionality at Grammarly, which is critical to realizing our vision of improving lives by improving communication.
To facilitate this mission, the Engineering Manager will coach, mentor, and support the team through product development and collaboration with product managers. They will also guide the team to propose and implement the best practices for scaling ML features at Grammarly across all phases of a feature's lifecycle, from fast iterative experimentation to product development and support. The Engineering Manager will also provide direction for project investments, prioritization, and engineering resource allocation, as well as coordinate with stakeholders.
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 Engineering Manager, you will lead the Machine Learning Engineering team and collaborate across multiple offices with research scientists, computational linguists, and product managers to ship delightful user experiences across various interfaces. You will influence and fundamentally change the way Grammarly engineering delivers ML-powered features.
In this role, you will:

• Guide the team to operating services at internet scale with high availability and reliability.
• Propose and implement the best engineering and research practices for scaling ML-powered features at Grammarly, with a goal to enable the fast iteration of and efficient experimentation with novel features.
• Help drive engineering-wide initiatives with other engineering leaders.
• Be an effective manager by strongly advocating for and promoting the team.
• Contribute to and influence the ML infrastructure roadmap based on the feedback from internal customers.
• Build and enhance consumer and enterprise intelligence features in grammatical error correction and text semantics, such as tone and summarization.

We're looking for someone who

• Embodies our EAGER values-is ethical, adaptable, gritty, empathetic, and remarkable.
• Is able to collaborate in person in San Francisco 4 weeks per quarter.
• Is a strong coder, with a good understanding of algorithms and data structures.
• Has experience with native development, as most of our code is in C++.
• Has experience developing machine learning models.
• Has-as a plus-experience with natural language processing or model distillation.

Support for you, professionally and personally

• Professional growth : We hire people we trust and 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, 401(k) matching, 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 race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Grammarly will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance. Grammarly is an equal opportunity employer and participant in the US Federal E-Verify program.
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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