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About This Role
About the Role
We are seeking a highly skilled, detail\-oriented Research Scientist with a strong Mathematical and Statistical background to join our team in Irvine, CA. In this role, you will research, design, and optimize the mathematical models behind our casino games—particularly slot machines—ensuring they are engaging, profitable, and compliant with global regulatory standards. You will collaborate with game designers, product managers, and engineers in a fast\-paced, on\-site environment, driving both research and product impact.
We're looking for a dedicated researcher in Mathematics, Statistics, or a related field, with expertise in probability theory, statistical modeling, and game mathematics/quality assurance. Fluency in Chinese is required, and you must be able to work on\-site in Irvine, CA.
Responsibilities
Game Mathematics Design \& Optimization
- Develop and refine core math models for slot machines and other casino games, ensuring they meet target Return to Player (RTP) rates, hit frequencies, and volatility goals.
- Balance player engagement, regulatory requirements, and long\-term profitability through innovative mathematical solutions.
Probability \& Bonus Mechanism Development
- Design and implement random mechanics, bonus rounds, free spins, jackpots, and other reward systems, verifying accuracy through combinatorial analysis and detailed probability calculations.
- Conduct detailed statistical analysis and develop suitable quantitative indices to describe the game performance accurately.
- Perform large\-scale simulations and data analyses (using tools like Excel, Python, MATLAB, R, or custom code) to forecast game performance, validate math models, and optimize player retention.
- Thoroughly test and verify mathematical outcomes, ensuring they align with intended player experiences and business objectives.
Regulatory Compliance \& Certification Support
- Prepare mathematical models, simulation reports, and documentation for certification by global regulatory bodies (e.g., GLI, BMM), ensuring international compliance across North America, Europe, and Asia.
Cross\-Functional Collaboration
- Work closely with designers, developers, product managers, and marketing teams to translate complex math concepts into compelling gameplay, clear player communication, and userfriendly interfaces.
- Handle multiple projects simultaneously, providing ongoing updates and constructive feedback while navigating creative conflicts in a consensus\-driven environment.
Field Research, Market Analysis \& Continuous Improvement
- Stay current on industry trends, player behavior, and competitive products, using insights to shape innovative game mechanics.
- Play\-test in\-development games and analyze live performance data, identifying opportunities to improve math models, game features, and overall player satisfaction.
- Maintain comprehensive design documentation (e.g., game concepts, par sheets, pay tables, control files) and ensure effective communication with all stakeholders.
Basic Qualifications
- Master's in Mathematics, Statistics, Applied Mathematics, or a closely related field (Required).
- Strong expertise in combinatorics, probability theory, and statistics, with demonstrable skill in mathematical modeling for game design.
- Experience with simulation/programming tools such as Python, MATLAB, R, C/C\+\+/C\#, or equivalent, for building prototypes, simulators, and data analyses.
- Fluency in Chinese (Required) and ability to communicate complex math concepts to both technical and non\-technical audiences.
- Familiarity with regulatory bodies (GLI, BMM, or comparable) and gaming compliance standards.
- Must be able to work on\-site in Irvine, CA 92618\.
Preferred / Nice to Have
- PhD in Mathematics, Statistics, Applied Mathematics, or a related field.
- Research experience with demonstrated success and publications in relevant fields.
- Experience with both land\-based and online casino games.
- Experience in game mathematics, quality assurance, or mathematical validation for casino games (e.g., slot machines).
- Proficiency in simulation/programming tools such as Python, MATLAB, R, C/C\+\+/C\#, or equivalent, for building prototypes, simulators, and data analyses.
- Knowledge of player behavior modeling, player lifetime value estimation, and retention analysis.
- Exposure to machine learning techniques for predictive modeling and game optimization.
- Experience with algorithm development and optimization.
- Passion for gaming across multiple genres and a creative yet analytical approach to innovative game design.
Pay: From $100,000\.00 per year
Benefits:
- Dental insurance
- Health insurance
- Life insurance
- Paid time off
- Parental leave
- Vision insurance
Language:
- Chinese (Required)
Ability to Commute:
- Irvine, CA 92618 (Required)
Ability to Relocate:
- Irvine, CA 92618: Relocate before starting work (Required)
Work Location: In person
Role Details
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 4,133 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Bitus Labs LLC, this role fits into their broader AI and engineering organization.
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 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.
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 $223,400 based on 307 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778.
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.
Bitus Labs LLC AI Hiring
Bitus Labs LLC has 3 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer. Based in Irvine, CA, US.
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 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.
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.
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 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.
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.
Frequently Asked Questions
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