---
title: 'Sr. Model Engineer at Cursor'
canonical: 'https://feeny.ai/job/sr-model-engineer-cursor-palo-alto-6f6jsqa4s07f'
type: 'job'
last_seen: '2026-11-10'
---

# Sr. Model Engineer at Cursor

- **Company:** Cursor
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-11-10
- **Last confirmed live:** 2026-11-10
- **Apply:** https://jobs.ashbyhq.com/cursor/dc69aeae-9cc4-4c57-aeab-560a8bc62d97

## Job description

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. Sr. Model Engineer SpaceXSI is building Super Intelligence to help humanity understand the universe. We train frontier coding agents and scale RL on real user data to make them increasingly effective. We're looking for Research Scientists who can drive effective RL or mid-training research in a small-team setting. You'll own ambiguous, hard research problems end-to-end: forming hypotheses, designing experiments, building the training/eval/data needed to test them, and pushing results into the next model.

## RESPONSIBILITIES:

- Design and run rigorous experiments that turn research ideas into measurable gains in model capability
- Improve data recipes through data quality, deduplication, and mixture experiments
- Define what makes RL data and rewards good, including grader design and preventing reward hacking
- Advance training science, from architecture and scaling experiments to post-training recipes for coding and computer-use agents
- Build evals and targeted tasks that expose model weaknesses and guide where the team invests next
- Partner with engineers to take promising results from small experiments to frontier-scale training runs

## BASIC QUALIFICATIONS:

- 3+ years of hands-on experience training or post-training large neural networks (1B+ parameters), including work on pre-training, fine-tuning, or RL-based methods (e.g., RLHF, DPO).
- Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++

## PREFERRED SKILLS AND EXPERIENCE:

- Able to handle ambiguous research tasks with little guidance, and to own a research direction end to end
- Care an unusual amount about data quality, and can dive into the data when appropriate
- Truth seeking, aiming to learn more about the science than to prove your ideas are correct
- Experience with RL algorithms for language models, scaling laws, or building RL environments and evals
- Experience with distributed training at scale and debugging problems that only show up at scale
- Experience training frontier-scale models
- Strong background in RL and machine learning fundamentals
- An excellent programmer and software engineer, comfortable working across the research stack in Python and PyTorch or JAX
- Hands-on experience training large models, through pretraining, post-training or RL
- A track record of original work in ML, such as new methods or real improvements, shown through research, open source or production impact
- MS or PhD in CS, ML, math, physics or a related field, or equivalent research experience

## ADDITIONAL REQUIREMENTS:

- Onsite role: must be able to work in person at the Palo Alto office

## COMPENSATION AND BENEFITS:

The annual compensation range for this role is listed below. Annual Salary: $220,000 - $357,000 USD Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience. Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

## About Cursor

## Company Overview
- **One-liner**: Cursor is an AI coding agent and software development environment that enables developers to build, test, and ship software using natural-language instructions and autonomous agents.
- **Entity Type**: Private (pending acquisition by SpaceX/xAI)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Michael Truell, Sualeh Asif, Aman Sanger, Arvid Lunnemark

## Core Business
- **Primary industry**: Artificial intelligence, developer tools, software development
- **Target customers**: B2B (enterprise, SMB, individual developers); trusted by over half of the Fortune 500
- **Mission/purpose**: To build the future of software development and help engineers "engineer anything"

## Products & Services
- **Cursor (AI Coding Agent)**: The flagship product — an AI-powered code editor and agent that searches codebases, edits files, runs terminal commands, and completes multi-step programming tasks from natural-language instructions. Available as a desktop IDE, web app, mobile app (iOS), and CLI.
- **Bugbot**: A code-review tool integrated with GitHub pull requests that autonomously detects bugs and issues.
- **Composer Models**: A family of proprietary agentic coding models (Composer, Composer 1.5, Composer 2, Composer 2.5) trained with reinforcement learning for long-running coding tasks.
- **Cursor Automations**: Always-on agents that run on schedules or triggers to build, maintain, and fix software.
- **Cloud Agents**: Agents that run in their own cloud environments to build, test, and demo features end-to-end.
- **Graphite**: A separate product acquired by Cursor (formerly a stack-based Git workflow tool).

## Market Standing
- **Valuation**: $29.3 billion (Series D, November 2025); pending acquisition by SpaceX/xAI at $60 billion (announced June 16, 2026)
- **Key Metric**: $3 billion+ Annual Recurring Revenue (ARR) as of May 2026
- **Notable Investors**: Accel, Coatue Management, Thrive Capital, OpenAI Startup Fund, Google, Nvidia; angel investors include Nat Friedman (former GitHub CEO) and Arash Ferdowsi (Dropbox co-founder)
- **Growth Signals**: Crossed $100M ARR in Jan 2025, $500M ARR by June 2025, $1B ARR by Nov 2025, and $3B ARR by May 2026. Headcount grew from ~300 (2025) to 579 (mid-2026). Expanding into mobile, Jira integration, and enterprise features.

## Competitive Advantages
- **Proprietary coding models (Composer series)** trained with reinforcement learning specifically for software development tasks — a deep technical moat
- **Complete codebase understanding** at any scale, enabling agents to work contextually across large, complex codebases
- **Multi-model flexibility**: Integrates models from OpenAI, Anthropic, Gemini, xAI, and their own models, letting users choose the best tool per task
- **Agentic infrastructure**: Agents that run autonomously, in parallel, and across environments (terminal, Slack, GitHub, Jira, cloud)
- **Massive adoption**: Trusted by over half the Fortune 500 and millions of developers — strong network effects and brand lock-in

## Strategic Focus
- **Scaling agentic capabilities**: Moving from assisted coding to fully autonomous software development agents
- **Enterprise expansion**: Building admin controls, SSO, compliance features, and usage analytics for large organizations
- **Platform ecosystem**: Expanding into adjacent tools (Jira, Slack, GitHub, mobile) to embed agents everywhere developers work
- **Model research**: Continued investment in training frontier coding models with reinforcement learning and synthetic data
- **Post-acquisition integration with xAI**: Leveraging SpaceX/xAI compute and infrastructure for even larger models

## Why Work Here
- **Mission-driven research environment**: Cursor describes itself as "an applied research team focused on building the future of software development" — a rare blend of R&D and product engineering
- **Talent density**: The company "obsesses over talent to an unusual degree" and designs itself as "a haven for self-motivated individual contributors"
- **Rapid growth trajectory**: From 0 to $3B ARR in ~4 years — employees work on products used by millions and see massive scale
- **Compensation**: Competitive for AI/engineering talent; top-of-market salaries and equity in a high-valuation private company
- **Work policy**: Mix of in-office (San Francisco, New York) and remote roles; many engineering roles are on-site
- **Engineering culture**: Two-day on-site final interviews with the core team; no AI tools allowed in first-round coding interviews — they value raw problem-solving
- **Team composition**: 579 employees with strong talent density from Stripe, Figma, Notion, Vercel, Graphite, Slack, Rubrik, and Plaid
- **Recent departures to**: Anthropic, OpenAI, Google, AWS — alumni are highly sought after

## Sources
1. [cursor.com](https://cursor.com)
2. [cursor.com/careers](https://cursor.com/careers)
3. [LinkedIn](https://www.linkedin.com/company/cursorai)
4. [Wikipedia](https://en.wikipedia.org/wiki/Cursor_(company))
5. [JobsByCulture](https://jobsbyculture.com/blog/working-at-cursor-2026)

## Other roles at Cursor

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