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Machine Learning Engineer, Fraud & Abuse
Superhuman🇺🇸In-Person - San Francisco, CA$250K–$385K/yr4mo ago
Role Snapshot
Machine Learning Engineer at Superhuman (formerly Grammarly) developing advanced ML systems to identify abusive users and fraudulent content in shared documents. This mission-critical role protects millions of users through innovative AI-powered fraud detection and prevention.
Key Responsibilities: Lead development of ML models for detecting abusive users and fraudulent content in shared environments, analyze user behavior and document content for spam/scam detection, and own critical detection pipelines from development through deployment. Integrate cutting-edge NLP and LLM approaches to identify suspicious patterns in real-time and deliver rapid iterations from concept to production.
Skills & Tools: Extensive expertise in machine learning, natural language processing, and large language models with demonstrated experience building LLM-based products. Strong focus on end-user experience, ability to work independently with minimal guidance, and proficiency in cross-functional collaboration within fast-paced environments.
Qualifications: MS or PhD in Computer Science with 5+ years of industry experience as a machine learning engineer or applied research scientist. Deep understanding of modern ML, NLP, and LLM algorithms with proven ability to proactively manage multiple projects and execute work efficiently.
Location: San Francisco, California
Compensation: $250K–$385K/yr
Job Description
The full job description is available on Superhuman's website.
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