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About This Role
About 1X
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We’re building humanoid robots that work in home \- doing the chores, handling the tasks, and giving people their time back. Simple, but it’s not.
To do this right, we have to solve robotics, AI, manufacturing \- at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you’re inspired by this, you’ll thrive here. We’ve been at this since 2014 and we’re at the point where the hard problems are behind us and the hard work is in front of us.
NEO is our flagship \- a home robot designed to move, learn, and operate in the real world alongside real people. We’re not demoing it \- we’re shipping it. We’re excited to meet you, if this excites you.
If you’ve spent your career working on problems that matter and want to see them actually reach the world \- this is that moment. We’re scaling, we’re hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time \- safely creating abundance for all.
About the Team
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The Applied AI team owns all of the systems and services that integrate AI into the NEO platform including supporting data infrastructure for the World Model Lab. They ship platform APIs that allow our developers to collect data for fine\-tuning, deploy inference at scale, and integrate AI elsewhere in the robot software stack.
Your Charter
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Build platform APIs for high\-quality training data for our new world model. This will involve APIs for data validation, auto\-captioning/annotation, and validation. You’ll operate at high scale, support a wide variety of developers, and work closely with our internal World Model team to pretrain a new world model. You will also find opportunities to integrate AI in other systems elsewhere in the stack.
Key Outcomes
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- Design, build, and ship production features for AI world models, from data collection through inference
- Build rigorous evaluation, data pipelines, and captioning APIs tightly integrated into simulators and robot hardware
- Optimize systems for latency, cost, and quality
- Work closely with world model researchers, product engineers, and customers to build systems that are reliable and easy to use
- Stay current with new developments in AI and bring recommendations to the platform and research teams.
Key Competencies
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- Deep expertise building developer tooling, simulation platforms, or game engine infrastructure.
- Strong systems thinking with experience designing scalable content pipelines and engineering workflows.
- Experience creating easy to use tools that empowers developers, designers, or technical artists.
- Excellent software engineering skills with a focus on performance, maintainability, and automation.
- Comfortable driving technical direction across multidisciplinary teams in a fast\-moving startup environment.
Minimum Requirements
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- 5\+ years of software engineering experience, with a meaningful portion spent building and shipping ML\- or AI\-powered systems in production.
- Strong programming skills in Python and JavaScript/TypeScript and proved experience building expandable, testable, and reliable software.
- Hands\-on experience with modern AI/ML, AI frameworks, and cloud deployment
- Clear communication and collaboration to lead projects independently
Preferred Skills
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- Experience with shipping AI/ML systems at high scale.
- Contributions to open\-source AI/ML projects or publications
- Domain experience in robotics
What does a successful 1X Team Member look like:
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Team members at 1X who thrive here are builders. They move fast, own their work completely, and treat time like it’s the one thing you can’t get back \- because it is. They say what they mean, finish what they start, and hold themselves to a standard before anyone has to ask. We push each other to be better, and we do it with honesty and respect.
Benefits
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- Comprehensive medical, dental, and vision coverage
- Generous paid time off, company holidays, and parental leave
- 401(k) plan with company match (100% on the first 3% of contributions, 50% on the next 2%)
- Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA) options
- Commuter benefits (transit and parking)
- Short\-term and long\-term disability, and life insurance
- Employee Assistance Program (EAP) for mental health, financial, and personal support
- Onsite snacks and catered lunches
Equal Opportunity Employer
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1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, justice system impact, or any other characteristic protected under applicable federal, state, or local law.
Compensation Range: $250K \- $300K
Salary Context
This $250K-$300K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At 1X, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($275K) sits 26% above the category median. Disclosed range: $250K to $300K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
1X AI Hiring
1X has 1 open AI role right now. They're hiring across AI Software Engineer. Based in San Carlos, CA, US. Compensation range: $300K - $300K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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