Machine Learning Engineer, Fraud & Abuse Hybrid - San Francisco Apply

Grammarly • San Francisco, CA

7d • Hybrid

About The Position

We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you will be at the heart of our company's transformation.

Protect Shared Documents:
 Lead the development of advanced machine learning systems to identify abusive users and fraudulent content, with a special focus on documents and content shared between users.
Analyze Content and Behavior:
 Build models that evaluate both document content and user behavior, allowing for nuanced and effective detection of spam, scams, and manipulative activity within shared environments.
Own Key Detection Pipelines:
 Develop, deploy, and maintain critical systems for monitoring documents, interactions, and sharing patterns, providing proactive interventions to keep collaborative workspaces safe.
Integrate Leading AI Approaches:
 Operate at the forefront of fraud prevention by leveraging the latest advances in NLP and machine learning to understand, flag, and stop suspicious patterns in real time.
High-Impact, Mission-Aligned Work:
 Join a focused, mission-driven team where your contributions directly protect millions of users. Enjoy autonomy, rapid iteration, and the chance to make decisions that shape the future of secure collaboration.
Deliver Results Quickly:
 Move swiftly from concept to deployment, building solutions that enable safe document sharing and support Superhuman's global user base.

Requirements

• MS / PhD in Computer Science.
• 5+ years of industry experience as a machine learning engineer or applied research scientist.
• A deep understanding of modern algorithms and approaches to ML, NLP, and LLMs.
• Experience building LLM-based products.
• A deep care about the end-user experience and strives to ensure high quality.
• Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments.

Responsibilities

• Lead the development of advanced machine learning systems to identify abusive users and fraudulent content, with a special focus on documents and content shared between users.
• Build models that evaluate both document content and user behavior, allowing for nuanced and effective detection of spam, scams, and manipulative activity within shared environments.
• Develop, deploy, and maintain critical systems for monitoring documents, interactions, and sharing patterns, providing proactive interventions to keep collaborative workspaces safe.
• Operate at the forefront of fraud prevention by leveraging the latest advances in NLP and machine learning to understand, flag, and stop suspicious patterns in real time.
• Move swiftly from concept to deployment, building solutions that enable safe document sharing and support Superhuman's global user base.

Benefits

• 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
• 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
• Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
• Annual professional development budget and opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree