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About This Role
About Exponent:
Exponent is the only premium engineering and scientific consulting firm with the depth and breadth of expertise to solve our clients’ most profoundly unique, unprecedented, and urgent challenges.
Our vision is to engage multidisciplinary teams of science, engineering, and regulatory experts to empower clients with solutions that create a safer, healthier, more sustainable world. For over five decades, we've connected the lessons of past failures with tomorrow's solutions to advise clients as they innovate technologically complex products and processes, ensure the safety and health of their users, and address the challenges of sustainability.
Join our team of experts with degrees from top programs at over 500 universities and extensive experience spanning a variety of industries. At Exponent, you’ll contribute to the diverse pool of ideas, talents, backgrounds, and experiences that drives our collaborative teamwork and breakthrough insights. Plus, we help you grow your career through mentoring, sponsorship, and a culture of learning. Thanks for your interest in joining our team! Key statistics:* 950\+ Consultants
- 640\+ Ph.D.s
- 90\+ Disciplines
- 30\+ Offices globally
Our Opportunity:
We are currently seeking a Machine Learning User Research Scientist for our Data Sciences Practice in New York, NY. In this role, you will work as part of a team to plan and execute global data collection efforts, utilize and improve next\-generation products, and optimize internal and external programs to support clients in the consumer electronic industry.
You will be responsible for:
- Supporting a range of consulting activities related to large\-scale local and global programs to build custom datasets for machine learning algorithms including protocol development, data collection, data management, and analysis
- Providing operational support for prototype hardware and software systems including system validation and troubleshooting
- Actively solving technical and logistical problems in a fast\-paced environment
- Creating and leading ad hoc interdisciplinary teams comprised of consultants from Data Sciences, Human Factors, Health Sciences, and Engineering Sciences
- Developing data analysis and visualization tools related to project management, demographics, and human\-centered data
- Developing and Maintaining client relationships
You will have the following skills and qualifications:
- Ph.D. in Electrical Engineering, Computer Engineering, Physiology, Human Factors, or a related engineering/scientific field (such as Applied Mathematics, Computer Science, Cognitive Science, Applied Physics, Industrial Engineering, Mechanical Engineering, or Robotics)
- Ability to take an ambiguous question, use data to draw insights, and convey the results to a wide range of audiences
- Demonstrated experience and expertise in one or more of the following areas:
- + Advanced sensing technology
+ Networking data analysis and visualization
+ Developing and executing user research studies using appropriate, quantitative, and qualitative methods to produce tactical, strategic, actionable, and durable insights that inform design and development
+ Experience in programming or scripting languages like Python, Java, Perl, MATLAB
+ Experience in instrumentation, data acquisition, and data processing
+ Operations optimization
+ Experience in user studies design and execution with human subjects
+ Machine learning data set design or optimization
+ Dynamic system modeling and control
- The desire to work with a diverse set of clients and engage in work outside of the traditional data science field
- Strong practical engineering ability combined with leadership and project management skills
- Excellent verbal and written communication skills
- Ability to work independently and in multidisciplinary teams
- Ability to travel to a variety of global locations to support project work (up to 30% travel)
- Presently legally authorized to work in the United States. No immigration sponsorship or processing required.
*Applicants are encouraged to submit a CV (Curriculum Vitae) with publications (feel free to include publications that are in review or pending) \[not restricted to 1 page].*
Life @ Exponent:
To learn more about life at Exponent and our impact, please visit the following links:
https://www.exponent.com/careers/life\-exponent
https://www.exponent.com/company/our\-impact
Attracting, inspiring, developing, and rewarding exceptional people with diverse backgrounds and expertise are central to our corporate culture. Our diverse team allows us to provide better value to our clients and enjoy an enriched work environment.
Our firm is committed to offering a variety of programs and resources to support health and well\-being. We believe that providing competitive benefits as well as compensation and recognition programs empowers our staff to do work that makes a difference.
Work Environment:
At Exponent, we have found that in\-person interactions deepen employee engagement and are crucial for development, for realizing the full potential of our talented and diverse teams, and for building a more inclusive workplace where all have a sense of belonging. In our offices, you can expect a supportive culture and a collaborative, dynamic, multi\-disciplinary work environment. Our consultants engage in\-person in the office unless they are traveling for client work or other business activities.
We value the rich lives our colleagues enjoy outside of work and understand that work/life balance is critical to our employees and their well\-being. Consultants have the autonomy to balance their work and personal schedules so you can meet with clients, visit inspection sites, attend conferences, and make time for priorities outside of work, too. It is this flexible, agile work style and working hours that allow our teams to drive innovation and results in their own ways, while meeting the needs of clients. \#LI\-Onsite
Compensation:
Our consultants are rewarded for their technical and business contributions and have an opportunity to plan for future success and career growth. Exponent's total compensation plan is consistent with its expectations of the quality and quantity of work performed and with the professional standards set by Exponent. At the Associate and Senior Associate level, total compensation includes base salary, bi\-weekly bonuses for high\-intensity efforts, annual bonus and 401(k) employer contribution of 7% of base salary.
The base salary range for this position is dependent on experience and capabilities which will be assessed during the interview process.
Salary Range: USD $130,000\.00 \- USD $135,000\.00 /Yr. Benefits you will enjoy:
Access benefits information on our Life@Exponent page:
https://www.exponent.com/careers/life\-exponent
Exponent is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, veteran status, disability, sexual orientation, gender identity, or any other protected status.
If you need assistance or accommodation due to a disability, you may email us at HR\[email protected].
Job Locations: US\-NY\-New York
Salary Context
This $130K-$135K range is in the lower quartile for Research Scientist roles in our dataset (median: $183K across 109 roles with salary data).
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 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Exponent, 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 280 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($132K) sits 41% below the category median. Disclosed range: $130K to $135K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Exponent AI Hiring
Exponent has 2 open AI roles right now. They're hiring across Research Scientist. Based in New York, NY, US. Compensation range: $135K - $135K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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