Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now!
Grammarly
Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now!
Job Description
Machine Learning Engineer, Agents - Grammarly Careers in San Francisco
Role Overview
Join Grammarly's AI Agents team as a Machine Learning Engineer and shape the future of productivity. Now part of Superhuman, Grammarly is building the world's most powerful AI productivity platform. We're creating a groundbreaking platform where multiple AI agents collaborate seamlessly to solve complex tasks, leveraging Superhuman's ubiquitous UI.
In this high-impact role, you'll develop core orchestration, routing, and planning systems that power intelligent agent collaboration. You'll build ML models for search ranking, proactive suggestions, and context-aware assistance that anticipates user needs before they arise. This is your chance to work at the forefront of AI innovation, shipping features used by 40+ million people worldwide.
Our hybrid model in San Francisco combines focused deep work with energizing in-person collaboration, fostering trust, innovation, and team culture. If you thrive in fast-paced environments with high autonomy, this is your opportunity to make a lasting impact on enterprise productivity.
Key Responsibilities
- Architect and implement core ML systems for AI agent orchestration and multi-agent collaboration
- Develop advanced search ranking models that understand complex user intent and context
- Build proactive suggestion engines using reinforcement learning and predictive modeling
- Design routing algorithms that intelligently delegate tasks across specialized AI agents
- Create planning systems for task decomposition and multi-step reasoning workflows
- Integrate state-of-the-art LLMs and foundation models into production-grade experiences
- Own end-to-end ML pipelines including data processing, training, evaluation, and deployment
- Optimize model serving infrastructure for low-latency, high-throughput inference at scale
- Design and execute A/B experiments measuring ML system impact on user productivity
- Collaborate cross-functionally with product, design, and engineering teams
- Implement robust monitoring, alerting, and observability for production ML systems
- Research and prototype cutting-edge techniques in agentic AI and collaborative intelligence
- Mentor junior engineers and contribute to technical strategy
Qualifications
Technical Expertise:
- 5+ years of machine learning engineering experience with production ML deployments
- Deep expertise in NLP, deep learning, and large language models
- Proven experience building search ranking and recommendation systems
- Strong Python skills with PyTorch/TensorFlow proficiency
- Experience with ML infrastructure, model serving (TensorRT, ONNX, Triton), and orchestration (Ray, Kubeflow)
Product & Systems Thinking:
- Demonstrated ability to ship ML features serving millions of users
- Strong systems design skills for scalable, reliable ML platforms
- Experience working in ambiguous environments with high autonomy
- Excellent product sense and user-centric ML development approach
Education & Background:
- BS/MS/PhD in Computer Science, Machine Learning, Statistics, or related field
- Portfolio of impactful ML projects (GitHub, publications, or production systems)
Salary & Benefits
Salary range: $185,000 - $265,000 base + equity + benefits (San Francisco market). Total compensation includes competitive equity in a high-growth AI company valued at billions.
- Hybrid SF work model with flexibility
- Comprehensive medical, dental, vision coverage
- 401(k) with generous matching
- Unlimited PTO + recharge weeks
- 16+ weeks parental leave
- $2,000+ annual learning stipend
- Full home office setup
- Weekly catered lunches & offsites
- Relocation support available
Why Join Grammarly?
Grammarly (now Superhuman) isn't just another productivity tool—it's the AI platform redefining how 40M+ people work. Our suite spans writing assistance, collaborative workspaces, intelligent email, and proactive AI agents. We're on a mission to eliminate busywork everywhere people work.
Impact at Scale: Your ML systems will power experiences for 50K+ organizations and 3K educational institutions worldwide.
Cutting-Edge AI: Work with the latest foundation models, agentic architectures, and production ML infrastructure.
High Ownership: Small teams, big impact. No bureaucracy—just results.
Exceptional Culture: Values-driven company with transparent leadership and genuine care for employees.
How to Apply
Ready to build the future of AI agents? Submit your resume, GitHub/portfolio link, and a brief note about your most impactful ML project. Our process includes:
- 30-min recruiter screen
- Technical deep-dive with ML team
- Systems design interview
- Live coding challenge
- Team fit & leadership chat
We review applications on a rolling basis. Top candidates hear back within 48 hours.
Locations
- San Francisco, California, United States
Salary
194,250 - 291,500 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning Engineeringintermediate
- AI Agent Developmentintermediate
- Natural Language Processingintermediate
- Deep Learning Modelsintermediate
- LLM Orchestrationintermediate
- Search Ranking Algorithmsintermediate
- Reinforcement Learningintermediate
- Python Programmingintermediate
- PyTorch Expertiseintermediate
- TensorFlow Proficiencyintermediate
- Model Deploymentintermediate
- Scalable ML Systemsintermediate
- Prompt Engineeringintermediate
- Multi-Agent Systemsintermediate
- Production ML Pipelinesintermediate
- A/B Testing Frameworksintermediate
- Cloud ML Infrastructureintermediate
- API Integrationintermediate
- Data Pipeline Engineeringintermediate
- Generative AIintermediate
Required Qualifications
- 5+ years of experience in machine learning engineering with production deployments (experience)
- Deep expertise in building and scaling AI agent orchestration systems (experience)
- Proven track record developing ML models for search ranking and recommendation systems (experience)
- Strong proficiency in Python, PyTorch, and TensorFlow (experience)
- Experience with large language models (LLMs) and prompt engineering (experience)
- Hands-on experience with multi-agent AI architectures and collaboration frameworks (experience)
- Demonstrated ability to ship ML systems serving millions of users (experience)
- Strong understanding of ML infrastructure, model serving, and monitoring (experience)
- Experience with cloud platforms (AWS, GCP, Azure) for ML workloads (experience)
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field (experience)
- Excellent problem-solving skills in ambiguous, fast-paced environments (experience)
- Strong communication skills and product sense for cross-functional collaboration (experience)
Responsibilities
- Design and build core orchestration systems for multi-agent AI collaboration
- Develop sophisticated ML models for search ranking and proactive suggestions
- Implement routing and planning algorithms for complex task decomposition
- Integrate cutting-edge LLMs and foundation models into production systems
- Own end-to-end ML pipelines from data processing to model deployment
- Optimize model inference latency and throughput for real-time user experiences
- Conduct A/B experiments to validate ML system improvements
- Collaborate with product teams to define ML requirements and success metrics
- Build scalable ML infrastructure supporting millions of daily predictions
- Monitor and maintain production ML systems with comprehensive observability
- Research and implement state-of-the-art techniques in agentic AI
- Contribute to responsible AI practices and model safety frameworks
- Mentor junior engineers and lead technical initiatives
Benefits
- general: Competitive salary with equity in a high-growth AI company
- general: Hybrid work model in San Francisco with flexible scheduling
- general: Comprehensive health, dental, and vision insurance coverage
- general: 401(k) matching program for retirement savings
- general: Unlimited PTO with encouraged recharge periods
- general: Generous parental leave policies (16+ weeks)
- general: Annual learning and development stipend ($2,000+)
- general: Home office setup allowance and equipment
- general: Weekly team lunches and company offsites
- general: Mental health support through dedicated programs
- general: Fitness reimbursement and wellness initiatives
- general: Employee stock purchase plan with discounts
- general: Relocation assistance for qualifying candidates
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now! @ Grammarly.
Related Books and Jobs
Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now!
Grammarly
Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now!
Job Description
Machine Learning Engineer, Agents - Grammarly Careers in San Francisco
Role Overview
Join Grammarly's AI Agents team as a Machine Learning Engineer and shape the future of productivity. Now part of Superhuman, Grammarly is building the world's most powerful AI productivity platform. We're creating a groundbreaking platform where multiple AI agents collaborate seamlessly to solve complex tasks, leveraging Superhuman's ubiquitous UI.
In this high-impact role, you'll develop core orchestration, routing, and planning systems that power intelligent agent collaboration. You'll build ML models for search ranking, proactive suggestions, and context-aware assistance that anticipates user needs before they arise. This is your chance to work at the forefront of AI innovation, shipping features used by 40+ million people worldwide.
Our hybrid model in San Francisco combines focused deep work with energizing in-person collaboration, fostering trust, innovation, and team culture. If you thrive in fast-paced environments with high autonomy, this is your opportunity to make a lasting impact on enterprise productivity.
Key Responsibilities
- Architect and implement core ML systems for AI agent orchestration and multi-agent collaboration
- Develop advanced search ranking models that understand complex user intent and context
- Build proactive suggestion engines using reinforcement learning and predictive modeling
- Design routing algorithms that intelligently delegate tasks across specialized AI agents
- Create planning systems for task decomposition and multi-step reasoning workflows
- Integrate state-of-the-art LLMs and foundation models into production-grade experiences
- Own end-to-end ML pipelines including data processing, training, evaluation, and deployment
- Optimize model serving infrastructure for low-latency, high-throughput inference at scale
- Design and execute A/B experiments measuring ML system impact on user productivity
- Collaborate cross-functionally with product, design, and engineering teams
- Implement robust monitoring, alerting, and observability for production ML systems
- Research and prototype cutting-edge techniques in agentic AI and collaborative intelligence
- Mentor junior engineers and contribute to technical strategy
Qualifications
Technical Expertise:
- 5+ years of machine learning engineering experience with production ML deployments
- Deep expertise in NLP, deep learning, and large language models
- Proven experience building search ranking and recommendation systems
- Strong Python skills with PyTorch/TensorFlow proficiency
- Experience with ML infrastructure, model serving (TensorRT, ONNX, Triton), and orchestration (Ray, Kubeflow)
Product & Systems Thinking:
- Demonstrated ability to ship ML features serving millions of users
- Strong systems design skills for scalable, reliable ML platforms
- Experience working in ambiguous environments with high autonomy
- Excellent product sense and user-centric ML development approach
Education & Background:
- BS/MS/PhD in Computer Science, Machine Learning, Statistics, or related field
- Portfolio of impactful ML projects (GitHub, publications, or production systems)
Salary & Benefits
Salary range: $185,000 - $265,000 base + equity + benefits (San Francisco market). Total compensation includes competitive equity in a high-growth AI company valued at billions.
- Hybrid SF work model with flexibility
- Comprehensive medical, dental, vision coverage
- 401(k) with generous matching
- Unlimited PTO + recharge weeks
- 16+ weeks parental leave
- $2,000+ annual learning stipend
- Full home office setup
- Weekly catered lunches & offsites
- Relocation support available
Why Join Grammarly?
Grammarly (now Superhuman) isn't just another productivity tool—it's the AI platform redefining how 40M+ people work. Our suite spans writing assistance, collaborative workspaces, intelligent email, and proactive AI agents. We're on a mission to eliminate busywork everywhere people work.
Impact at Scale: Your ML systems will power experiences for 50K+ organizations and 3K educational institutions worldwide.
Cutting-Edge AI: Work with the latest foundation models, agentic architectures, and production ML infrastructure.
High Ownership: Small teams, big impact. No bureaucracy—just results.
Exceptional Culture: Values-driven company with transparent leadership and genuine care for employees.
How to Apply
Ready to build the future of AI agents? Submit your resume, GitHub/portfolio link, and a brief note about your most impactful ML project. Our process includes:
- 30-min recruiter screen
- Technical deep-dive with ML team
- Systems design interview
- Live coding challenge
- Team fit & leadership chat
We review applications on a rolling basis. Top candidates hear back within 48 hours.
Locations
- San Francisco, California, United States
Salary
194,250 - 291,500 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning Engineeringintermediate
- AI Agent Developmentintermediate
- Natural Language Processingintermediate
- Deep Learning Modelsintermediate
- LLM Orchestrationintermediate
- Search Ranking Algorithmsintermediate
- Reinforcement Learningintermediate
- Python Programmingintermediate
- PyTorch Expertiseintermediate
- TensorFlow Proficiencyintermediate
- Model Deploymentintermediate
- Scalable ML Systemsintermediate
- Prompt Engineeringintermediate
- Multi-Agent Systemsintermediate
- Production ML Pipelinesintermediate
- A/B Testing Frameworksintermediate
- Cloud ML Infrastructureintermediate
- API Integrationintermediate
- Data Pipeline Engineeringintermediate
- Generative AIintermediate
Required Qualifications
- 5+ years of experience in machine learning engineering with production deployments (experience)
- Deep expertise in building and scaling AI agent orchestration systems (experience)
- Proven track record developing ML models for search ranking and recommendation systems (experience)
- Strong proficiency in Python, PyTorch, and TensorFlow (experience)
- Experience with large language models (LLMs) and prompt engineering (experience)
- Hands-on experience with multi-agent AI architectures and collaboration frameworks (experience)
- Demonstrated ability to ship ML systems serving millions of users (experience)
- Strong understanding of ML infrastructure, model serving, and monitoring (experience)
- Experience with cloud platforms (AWS, GCP, Azure) for ML workloads (experience)
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field (experience)
- Excellent problem-solving skills in ambiguous, fast-paced environments (experience)
- Strong communication skills and product sense for cross-functional collaboration (experience)
Responsibilities
- Design and build core orchestration systems for multi-agent AI collaboration
- Develop sophisticated ML models for search ranking and proactive suggestions
- Implement routing and planning algorithms for complex task decomposition
- Integrate cutting-edge LLMs and foundation models into production systems
- Own end-to-end ML pipelines from data processing to model deployment
- Optimize model inference latency and throughput for real-time user experiences
- Conduct A/B experiments to validate ML system improvements
- Collaborate with product teams to define ML requirements and success metrics
- Build scalable ML infrastructure supporting millions of daily predictions
- Monitor and maintain production ML systems with comprehensive observability
- Research and implement state-of-the-art techniques in agentic AI
- Contribute to responsible AI practices and model safety frameworks
- Mentor junior engineers and lead technical initiatives
Benefits
- general: Competitive salary with equity in a high-growth AI company
- general: Hybrid work model in San Francisco with flexible scheduling
- general: Comprehensive health, dental, and vision insurance coverage
- general: 401(k) matching program for retirement savings
- general: Unlimited PTO with encouraged recharge periods
- general: Generous parental leave policies (16+ weeks)
- general: Annual learning and development stipend ($2,000+)
- general: Home office setup allowance and equipment
- general: Weekly team lunches and company offsites
- general: Mental health support through dedicated programs
- general: Fitness reimbursement and wellness initiatives
- general: Employee stock purchase plan with discounts
- general: Relocation assistance for qualifying candidates
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Engineer, Agents Careers at Grammarly - San Francisco, CA | Apply Now! @ Grammarly.
Related Books and Jobs