Software Engineer, ML Research

Cursor1 months ago

Location

SF / NY

Type

Full Time

Salary

USD 180,000 – 300,000

Level

Senior

Role

ML Engineer

Posted

Jan 27, 2026

Full TimeSenior

The role

Summary

Cursor is seeking a Research Engineer to build training, inference, and data systems for frontier coding AI models. The role involves working directly with researchers to develop distributed ML infrastructure and scale reinforcement learning on real user data to automate coding.

What you'll do

Infrastructure Development: Build distributed training, inference, and reinforcement learning infrastructure to support frontier coding models

Research Support: Work directly with researchers to make progress repeatable and enable fast iteration cycles

Library Development: Write and maintain libraries that simplify large-scale data processing jobs for research teams

Data Pipeline Architecture: Architect systems that transform Cursor user data into effective training datasets for ML models

System Optimization: Optimize distributed systems performance for large-scale model training and inference workloads

End-to-End Ownership: Take full ownership of projects from architecture design through deployment and maintenance

Scalability Engineering: Design and implement systems that can handle massive scale data processing and model serving

Research Collaboration: Collaborate closely with ML researchers to translate research ideas into production-ready systems

What we look for

Technical

Distributed SystemsStrong background in building and maintaining large-scale distributed systems

Machine Learning InfrastructureExperience with ML training pipelines, model serving, and MLOps practices

Programming ProficiencyExpert-level proficiency in Python and systems programming languages like C++ or Rust

Cloud PlatformsHands-on experience with AWS, GCP, or Azure for ML workloads

Language Model UnderstandingStrong intuitions about how large language models work and their training requirements

Education

Computer Science DegreeBachelor's or Master's degree in Computer Science, Engineering, or related technical field

Alternative ExperienceEquivalent practical experience in distributed systems and ML infrastructure

Experience

Infrastructure Experience5+ years of experience building production-scale distributed systems

ML Systems Experience3+ years of experience with machine learning infrastructure and training systems

End-to-End DeliveryProven track record of architecting and shipping complex systems with high ownership

Research EnvironmentExperience working in fast-paced research environments with rapid iteration requirements

Skills

Required skills

Distributed SystemsDeep expertise in building scalable distributed systems architecture

Python ProgrammingAdvanced Python skills for ML infrastructure development

ML InfrastructureExperience with training pipelines, model serving, and MLOps

System ArchitectureAbility to design end-to-end systems with high performance requirements

Language ModelsUnderstanding of transformer architectures and training dynamics

Nice to have

Reinforcement LearningExperience with RL systems and human feedback integration

CUDA ProgrammingGPU programming experience for training optimization

Research BackgroundExperience working in AI/ML research environments

Code GenerationFamiliarity with code generation models and their unique challenges

Data EngineeringLarge-scale data processing and ETL pipeline experience

Compensation & benefits

Salary

USD 180,000 – 300,000 (annual)

Stock options

Available

Benefits

Equity Package

Significant equity stake in a fast-growing AI company with strong venture backing

Health Insurance

Comprehensive medical, dental, and vision insurance coverage

Office Environment

Beautiful offices in North Beach San Francisco and Manhattan with well-stocked libraries

Learning Budget

Professional development budget for conferences, courses, and technical resources

Flexible PTO

Unlimited paid time off policy to maintain work-life balance

Retirement Benefits

401(k) plan with company matching contributions

Relocation Support

Relocation assistance for moving to San Francisco or New York offices

Interview process

1
Initial Screen — Phone or video call with hiring manager to discuss background and role fit
2
Technical Phone Interview — 45-minute technical discussion covering distributed systems and ML infrastructure
3
System Design Interview — Design a large-scale ML training or inference system relevant to Cursor's needs
4
Coding Interview — Live coding session focused on algorithms and data structures
5
Research Collaboration Interview — Discussion with research team about supporting ML research workflows
6
Final Interview — Culture fit and leadership discussion with senior team members
7
Reference Checks — Professional references contacted before final offer