What Does a Research Scientist Do?
AI Research Scientists push the boundaries of what AI can do. They design novel architectures, develop new training techniques, and publish findings that advance the field.
A Typical Day
- Designing and running experiments on novel architectures
- Reading and building on recent research papers
- Writing papers and preparing conference submissions
- Collaborating with engineering teams on research-to-production transfer
- Mentoring junior researchers and interns
Required Skills
The most in-demand skills for Research Scientist roles, ranked by how often they appear in job postings.
- 1 Python 52 jobs
- 2 Rag 52 jobs
- 3 Rust 35 jobs
- 4 Aws 33 jobs
- 5 Tensorflow 24 jobs
- 6 Pytorch 23 jobs
- 7 Jax 6 jobs
- 8 Chain Of Thought 5 jobs
- 9 Llama 4 jobs
- 10 Embeddings 4 jobs
Salary & Compensation
Based on 60 job postings with disclosed compensation ranges.
Salary by Experience Level
| Level | Jobs | Salary Range |
|---|---|---|
| Mid Level | 40 | $152K - $219K |
| Senior | 20 | $186K - $270K |
Highest Paying Cities
| Metro | Jobs | Avg Salary Range |
|---|---|---|
| Los Angeles | 4 | $169K - $244K |
| San Francisco | 14 | $169K - $241K |
| Seattle | 19 | $161K - $238K |
| New York | 12 | $171K - $236K |
How to Get Started
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1
Build Your Foundation
A PhD in machine learning, computer science, or a related field is typically required. Strong publication records at top venues (NeurIPS, ICML, ICLR, ACL, CVPR) are expected.
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2
Master the Core Skills
Focus on the skills employers are asking for right now: Python, Rag, Rust. These are the top 3 skills appearing in Research Scientist job postings.
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3
Build Portfolio Projects
Ship real projects that demonstrate your skills. Open-source contributions, personal projects, or freelance work all count. Hiring managers want to see what you can build, not just what you know.
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4
Apply Strategically
Target companies actively hiring for this role. Top employers include Amazon.com, Meta, Amazon Web Services, Google. Tailor your resume to match the specific skills each company lists in their job descriptions.
Top Hiring Companies
Companies with the most Research Scientist job openings right now.
Career Progression
A typical career path for Research Scientist professionals.
Explore Research Scientist Careers
Related Roles
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 26,159 AI roles we're tracking, Research Scientist positions make up 0% of the market.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $257,000 based on 108 positions with disclosed compensation. This role's midpoint ($200K) sits 22% below the category median. Disclosed range: $163K to $236K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Frequently Asked Questions
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