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About This Role
Job Details:
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Job Description:
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The Opportunity
For nearly a decade, Intel's Neuromorphic Computing Lab\-together with a global ecosystem of 250\+ research groups\-has explored architectures, algorithms, and software inspired by the brain's extraordinary efficiency, scalability, and adaptability. Our Loihi series of research chips pioneered event\-driven, sparse, and massively parallel neuro\-inspired processing, fueling over 100 peer\-reviewed publications that validate its promise.
Now, we're entering an exciting new chapter: transforming these breakthroughs into real\-world products that will power the coming era of physical AI systems\-beyond the reach of GPUs and mainstream AI accelerators.
If you are passionate about pushing the boundaries of computing, from transistor\-level innovation to software abstractions, join us. Help define the next wave of AI technology that harnesses the proven advantages of Intel's neuromorphic computing technology with the versatility demanded by modern AI workloads.
Position Overview
Demonstrate the value of Intel's neuromorphic technologies by developing, implementing, and benchmarking algorithms for Intel's next\-generation neuromorphic architecture to enable applications in edge computing, signal processing, and autonomous systems for the era of physical AI with groundbreaking performance and efficiency.
This is a fixed\-term opportunity lasting approximately 12 months, with the potential for extension subject to the approval of both parties.
Responsibilities
- Support the development and optimization of advanced AI algorithms and signal processing applications for edge platforms powered by Intel's next\-generation neuromorphic architecture.
- Evaluate and benchmark signal processing algorithms on current and next\-generation neuromorphic hardware.
- Validate Intel's neuromorphic SDK by running real\-world signal processing workloads, gathering metrics, and proposing targeted software enhancements to the core development team.
- Present findings internally and to collaborators.
About the Organization
As part of Intel's CTO Office, you will join a vertically integrated incubation effort dedicated to bringing Intel's neuromorphic technology innovations to market. Our diverse team of engineers and researchers has pioneered sparse, event\-based, neuromorphic architecture over multiple generations and is now focused on commercializing the technology in future Intel and partner products.
Qualifications:
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Minimum qualifications
- Enrolled in a PhD program in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Physics, or a related field.
- 1\+ years of experience writing clean, efficient and modular Python and C\+\+ code.
- 1\+ years of experience developing AI models for signal processing, perception, reasoning, and control.
- 1\+ years of experience with software development best practices (OO design, testing, debugging, documentation, version control, code reviews).
- 1\+ peer\-reviewed publications.
Preferred qualifications
- Experience with edge AI HW accelerators or event\-based sensors.
- Exposure to neuroscience and neurobiology\-inspired algorithms.
- Experience in developing software for robotics or other real\-time control systems.
- Experience with profiling and benchmarking algorithms and hardware architectures.
- Strong problem\-solving and communication skills.
Job Type:
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Intel Contract Employee
Shift:
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Shift 1 (United States of America)
Primary Location:
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US, California, Santa Clara
Additional Locations:
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Business group:
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The mission of the Corporate Technology Office (CTO) is to incubate and develop strategically important emerging technologies that will serve as building blocks for computing systems and platforms of the future. This is done in collaboration with the business units of Intel, with the goal of transferring these technologies to the business units for productization and revenue generation.
Posting Statement:
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All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust
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N/A
Benefits
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We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel .
Annual Salary Range for jobs which could be performed in the US: $52,000\.00\-$200,000\.00
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job\-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on\-site at their assigned Intel site and off\-site. \* Job posting details (such as work model, location or time type) are subject to change.
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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
Salary Context
This $52K-$200K range is in the lower quartile for Research Scientist roles in our dataset (median: $183K across 117 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 4,133 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Intel Corporation, 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. This role's midpoint ($126K) sits 44% below the category median. Disclosed range: $52K to $200K.
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.
Intel Corporation AI Hiring
Intel Corporation has 4 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer. Positions span Santa Clara, CA, US, Hillsboro, OR, US. Compensation range: $188K - $413K.
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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