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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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1X Labs exists to provide the science and technology that enables human\-level, general\-purpose humanoids.
We identify the gap between what today's humanoids can do and what human\-level capability actually requires. From there, we pursue fundamental advances in sensing, actuation, materials, control, intelligence, and system architecture—carrying promising ideas all the way from research through product integration.
1X Labs is built for people who have achieved deep expertise in a particular field and are motivated by the challenge of solving problems that require multiple disciplines to advance together. Here, ideas are tested against reality, and research only matters if it ultimately ships.
Your Charter
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Bring us the idea, prototype, technology, or insight that you believe can materially advance humanoid performance.
This is not a role tied to a predefined roadmap. Instead, we are looking for exceptional technical individuals who have identified a meaningful capability gap and have a credible path toward closing it. Whether your work originates from research, industry, startups, or personal projects, we want to understand what you have built, what you've learned, and what you would pursue if given the resources to take it all the way.
As part of 1X Labs, you will be expected to transform ambitious technical ideas into evidence, working prototypes, and ultimately technologies that can survive the constraints of real products and real manufacturing.
Key Outcomes
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- Develop and validate technologies that meaningfully advance humanoid capability toward human\-level performance
- Demonstrate measurable improvements through rigorous experimentation, benchmarking, and real\-world validation
- Translate novel research ideas into working systems, prototypes, or platforms that can be evaluated and integrated
- Identify and overcome fundamental technical bottlenecks that limit current robotic performance
- Create credible paths from early\-stage research to scalable product implementation
Key Competencies
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- Exceptional technical depth in at least one relevant field, combined with the ability to reason across adjacent disciplines
- Strong bias toward execution, experimentation, and evidence\-based decision making
- Demonstrated ability to independently originate, develop, and validate ambitious technical ideas
- Comfort operating in highly ambiguous environments with minimal predefined structure
- Persistence and intellectual honesty when confronting difficult technical problems
Minimum Requirements
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- Applicants should demonstrate at least one of the following:
- First\-author or equivalent high\-impact scientific publication in a relevant technical field
- Development of a prototype, system, or technology that materially advanced the state of the art
- Experience founding or co\-founding a technical venture and successfully bringing deep\-technology products or technologies into the world
- Demonstrated track record of carrying complex technical ideas from concept through implementation and validation
- Clear evidence of exceptional technical achievement beyond traditional academic or industry credentials
Preferred Skills
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- Expertise in robotics, AI, controls, sensing, actuation, materials science, manufacturing, neuroscience, biomechanics, or other fields relevant to humanoid robotics
- Experience building and validating physical systems in real\-world environments
- Experience leading highly technical projects or research efforts
- Strong interdisciplinary reasoning across hardware, software, and system\-level challenges
- Demonstrated ability to translate research into deployable products
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.
Within 1X Labs, the most successful people are those who combine deep expertise with relentless curiosity. They are willing to challenge assumptions, test ideas against reality, and pursue difficult technical paths that others overlook. They care less about defending ideas and more about discovering what is true.
Application Prompt
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When applying, tell us:
- The performance gap you believe should be closed
- The technical foundation you already have (research, prototype, technology, or insight)
- Why existing approaches are insufficient
- What you would build and test first if constraints were removed
Compensation Range
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$250,000 \- $300,000 \+ Equity
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 Research Engineer roles in our dataset (median: $202K across 58 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 4,133 AI roles we're tracking, Research Engineer positions make up 2% of the market. At 1X, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills in Demand for This Role
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $260,000 based on 442 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($275K) sits 6% above the category median. Disclosed range: $250K to $300K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
1X AI Hiring
1X has 3 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer. Based in San Carlos, CA, US. Compensation range: $250K - $300K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 median, while Prompt Engineer roles sit at $140,000. 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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.
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