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About This Role
Who we are
With its A.I.\-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high\-density, end\-to\-end system – reinventing warehouse automation for increased efficiency, speed and flexibility.
What we need
We are seeking a highly analytical and practical engineer to model and evaluate complex, real\-world systems. This role focuses on translating physical system behavior—throughput, flow, and constraints—into simple, actionable mathematical models that inform product design, site configuration, and customer solutions.
This is not a purely theoretical or simulation\-heavy role. The ideal candidate is comfortable working from first principles, observing systems in operation, and building models that are directionally accurate and decision\-useful.
What you'll do
- Build mathematical models to estimate system throughput, capacity, and performance (e.g., cases/hour, cycle times, asset utilization)
- Translate on\-site observations into structured models (e.g., timing operations, identifying constraints, estimating flow)
- Support customer solutioning and pre\-sales by sizing systems and validating assumptions
- Work alongside leadership to pressure\-test system design in real time
- Bridge intuitive reasoning with structured modeling (e.g., “back\-of\-the\-envelope” scalable frameworks)
- Identify system bottlenecks (e.g., congestion, latency, resource constraints)
- Develop simple tools/templates to help teams consistently model and size systems
- Clearly communicate outputs to both technical and non\-technical stakeholders
What you'll need
- Background in Industrial Engineering, Mechanical Engineering, Applied Mathematics, or similar. PhD preferred.
- Minimum 7 years of experience in manufacturing, automation, or logistics environments.
- Throughput, capacity, or flow modeling
- Strong intuition for cycle times, bottlenecks, and system constraint, queueing / congestion concepts
- Ability to build models from first principle, imperfect or limited data
- Experience with tools like Python, Excel, or simulation tools is helpful but not required
- Excellent communication skills \- can explain complex ideas simply \& comfortable presenting to leadership and customers
Our environment
- Up to 30% travel may be required to customer sites and manufacturing locations.
- Employees must have a valid driver’s license and the ability to travel as needed.
- The employee is responsible for owning a credit card and managing expenses to be reimbursed on a biweekly basis.
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About Symbotic
Symbotic is an automation technology leader reimagining the supply chain with its end\-to\-end, AI\-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset for the world’s largest retail, wholesale, and food \& beverage companies. Applying next\-gen technology, high\-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency. As the backbone of commerce the Symbotic platform transforms the flow of goods and the economics of supply chain for its customers. For more information, visit www.symbotic.com .
We are a community of innovators, collaborators and pioneers who embrace our differences, because we know unique perspectives make us stronger and smarter. Every perspective matters. We depend on the collective voices of our employees, customers and community to help guide us as we build a better place to work – for you and the world. That’s why we’re proud to be an equal opportunity employer.
We do not discriminate based on race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.
The base range for this position in the posted location is $149,000\.00 \- $204,600\.00 however, base pay offered may vary depending on job\-related knowledge, skills, and experience. The compensation package includes medical, dental, vision, disability, 401K, PTO and/or other benefits.
Salary Context
This $149K-$204K range is below the median 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 Symbotic, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($176K) sits 21% below the category median. Disclosed range: $149K to $204K.
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.
Symbotic AI Hiring
Symbotic has 2 open AI roles right now. They're hiring across Research Scientist, Data Scientist. Based in Wilmington, MA, US. Compensation range: $204K - $204K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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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