Data science techniques, KPIs, Leadership Skill, Machine learning techniques, Marketing analytics, Optimization, Python Programming
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 to join our Marketing Technology team. This team is responsible for building systems that empower and enhance the company's marketing efforts and strategies. The person in this role will help shape marketing strategies, improve customer experiences, and optimize marketing campaigns. They will be responsible for leveraging data and advanced algorithms to improve the performance and efficiency of advertising campaigns with the goal of maximizing the return on investment (ROI) for ad spend and delivering targeted ads to the right audience.
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 Lead Machine Learning Engineer of the Growth org, you will transform how ML is applied to solve Growth problems. Your work will directly impact the topline KPIs that Growth team contributes to the overall business. You will lead research and exploration and help establish a robust ML development process for the organization. This is a high-impact role with a direct line of the channel with the area leads and the senior leadership team.
In this role, you will:
We’re looking for someone who
Support for you, professionally and personally
Compensation and benefits
Grammarly offers all team members competitive pay along with a benefits package encompassing the following and more:
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: $329,000-$399,000 (USD)
Zone 2: $254,000-$359,000 (USD)
Canada:
Zone 1: $279,000 – $361,000 (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.
Grammarly is a cloud-based typing assistant that reviews spelling, grammar, punctuation, clarity, engagement, and delivery mistakes in English language text. It uses artificial intelligence to identify and search for an appropriate replacement for the located error.