About Grammarly
The AI writing assistant that enhances your communication
Key Highlights
- Valuation of over $13 billion, among the top 10 US startups
- Over 500,000 integrations with applications and websites
- Headquartered in San Francisco, CA with 1001+ employees
- Raised $400 million in funding and profitable since inception
Grammarly, headquartered in the Financial District of San Francisco, CA, is an AI-powered writing assistant that enhances communication for millions of users. With over 500,000 integrations across various applications, Grammarly has evolved from a student-focused subscription service to a mainstream...
🎁 Benefits
Grammarly offers competitive benefits including equity, ample PTO, 401(k) matching, and support for home office setup. Employees enjoy catered lunches...
🌟 Culture
Grammarly fosters a culture centered on effective communication and innovation in AI technology. With a focus on remote work flexibility and a commitm...
Machine Learning Engineer • Mid-Level
Skills & Technologies
Overview
Grammarly is hiring a Machine Learning Engineer to develop advanced systems for detecting abusive users and fraudulent content. You'll work with Python and TensorFlow to analyze content and user behavior in San Francisco with a hybrid work model.
Job Description
Who you are
You have a strong background in machine learning and data analysis, with experience in developing models that can evaluate complex user behaviors and content. You are proficient in Python and have hands-on experience with machine learning frameworks such as TensorFlow. You understand the nuances of detecting spam and fraudulent activities, and you are passionate about building systems that enhance user safety and experience.
You thrive in collaborative environments and enjoy working closely with cross-functional teams to drive innovation. Your analytical mindset allows you to dissect problems and propose effective solutions, and you are comfortable communicating technical concepts to non-technical stakeholders. You are committed to continuous learning and staying updated with the latest advancements in AI and machine learning.
Desirable
Experience with large-scale data processing and familiarity with cloud platforms such as AWS or GCP would be advantageous. Knowledge of natural language processing (NLP) techniques is a plus, as it can enhance your ability to analyze user-generated content effectively.
What you'll do
As a Machine Learning Engineer at Grammarly, you will lead the development of advanced machine learning systems aimed at identifying abusive users and fraudulent content. You will build and refine models that evaluate both document content and user behavior, ensuring nuanced detection of spam and scams. Your work will directly contribute to enhancing the safety and integrity of shared documents within the Superhuman platform.
You will collaborate with product managers, data scientists, and software engineers to integrate machine learning solutions into existing products. This involves designing experiments, analyzing results, and iterating on models to improve accuracy and performance. You will also be responsible for documenting your processes and findings, ensuring that your insights are shared across the team.
In addition to model development, you will engage in code reviews and contribute to the overall architecture of machine learning systems. You will have the opportunity to mentor junior engineers and share your expertise, fostering a culture of learning and innovation within the team.
What we offer
Grammarly offers a flexible hybrid working model that allows you to balance focus time with in-person collaboration. You will be part of a dynamic team that is dedicated to unlocking the superhuman potential in everyone through AI. The company values diversity and inclusion, and you will have the chance to work on impactful projects that empower millions of users worldwide.
We encourage you to apply even if your experience doesn't match every requirement. Join us in our mission to enhance productivity and creativity through cutting-edge technology.
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