Machine Learning Engineer

Superhuman

. Shape Grammarly's evolution from a writing assistant into an AI-native productivity suite for enterprises .

Posted 10/26/2026full-timeUnited StatesMid-LevelSenior💰 $250,000 - $385,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning, Natural Language Processing, and Large Language Models, with a strong focus on user experience and product quality. Capable of developing and deploying ML models, managing agent workflows, and collaborating effectively in cross-functional teams.

Highest-signal resume keywords

Machine Learning EngineeringNatural Language ProcessingLarge Language ModelsProduct Quality ManagementCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNLPLLM DevelopmentAlgorithm DesignModel DeploymentSearch RankingProactive SuggestionsWorkflow PlanningAgent Memory ManagementEvaluation Design

Soft Skills

Independent WorkTask ManagementPrioritizationCollaborationAdaptability

Certifications & Qualifications

MS in Computer SciencePhD in Computer Science

Industry Keywords

AI Productivity SuiteUser ExperienceResults-Driven EnvironmentCross-Functional TeamsComplex Problem Solving

About the role

Key responsibilities & impact

Shape Grammarly's evolution from a writing assistant into an AI-native productivity suite for enterprises
Build a platform where multiple AI agents collaborate to solve complex user problems
Develop core orchestration, routing, and planning systems
Develop and deploy ML models for search ranking and proactive suggestions
Integrate ML components with the latest AI models
Plan multi-step agent workflows and select the appropriate agent or tool for each step
Manage agent memory and determine what the agent should remember about users
Expand user actions while keeping users in control
Build models to find and rank information across email, messages, and documents
Design evaluations to validate quality before shipping
Improve agent speed and operating cost without reducing answer quality

Requirements

What you’ll need

MS / PhD in Computer Science
5+ years of industry experience as a machine learning engineer or applied research scientist
Deep understanding of modern algorithms and approaches to ML, NLP, and LLMs
Experience building LLM-based products
Strong focus on end-user experience and product quality
Ability to work independently with minimal guidance
Ability to proactively manage tasks and priorities across multiple projects
Ability to analyze and execute work efficiently
Ability to collaborate effectively with cross-functional teams
Ability to thrive in fast-paced, results-driven environments

Benefits

Comp & perks

Excellent health care, including 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
Flexible sick time
Stipends for caregiving, pet care, wellness, home office, and more
Annual professional development budget and opportunities