PhD Applied Scientist, Routing

Symbotic LLC; Wilmington (MA); Hybrid; USD 72,000 - 74,000; Full time

Benefits offered by this job

Transportation

Housing

Medical

Dental

Vision

Disability

401K

PTO

Other benefits

Job summary

Symbotic is seeking an applied scientist intern with a passion for multi-agent planning to improve the performance and reliability of its systems. The Robot Routing team designs efficient, collision-free paths for dozens of robots across the transfer deck and explores deadlock resolution and time-space reservations.

This hybrid role is based at our Wilmington, MA headquarters, offering mentorship, projects, and opportunities to present findings at top conferences while contributing to real-world

Qualifications

• Pursuing PhD in CS, EE, Mech, Robotics or related field.
• Proficiency in one or more general-purpose programming languages: C++, Python, Java, or C#.
• Strong research background in combinatorial optimization, robotics planning, multi-robot systems, or ML.
• Publications at high-impact venues (e.g., CoRL, NeurIPS, ICML, ICRA, IJCAI).

Responsibilities

• Identify high-impact scenarios where AI Planning and ML can optimize Symbotic robotics software.
• Adapt state-of-the-art approaches or develop high-performance algorithms for multi-robot problems.
• Conduct simulations and experiments to validate multi-robot algorithm performance.
• Present results verbally and in writing, internally and at top-tier venues.

Skills

C++

Python

Java

C#

Robotics planning

Multi-robot systems

Machine learning

Education

Pursuing PhD in CS/EE/Mech/Robotics

Tools

Publications (Conferences/Journals)

Job description

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.

Timeframe: Summer (May-Aug 2027)

At Symbotic, Early Career talent plays a meaningful role in helping us reimagine the future of supply chain automation. Through our Internship and Co-op programs, students have the opportunity to contribute to real projects, collaborate with experienced engineers and business leaders, and gain hands‑on exposure to the technologies powering our end‑to‑end robotics and automation solutions. We are looking for curious, motivated students who are excited to solve complex problems, bring new perspectives to cross‑functional teams, and see their work make an impact in a fast‑moving, innovative environment. Along the way, Interns and Co‑ops are supported through mentorship, professional development, networking opportunities, and a robust calendar of events designed to help them build community and grow their careers. Symbotic offers transportation and housing benefits for students who meet our relocation requirements.

What we need

Symbotic is looking for an applied scientist intern with a passion for multi‑agent planning to improve the performance and reliability of our systems as we rapidly scale our product and organization. The Robot Routing team plans highly efficient, collision‑free paths between the storage structure and the inbound/outbound cells of our system for dozens of robots traversing the transfer deck. The right candidate is excited about concepts like deadlock resolution and time‑space reservations. This is a hybrid position based at our headquarters in Wilmington, MA.

What you’ll do

• Identify high‑impact scenarios where AI Planning and machine learning can be applied to optimize the Symbotic robotics software.
• Adapt state‑of‑the‑art approaches or develop high‑performance algorithms to solve real‑world multi‑robot problems.
• Conduct simulations and experiments to validate the performance of the multi‑robot algorithms.
• Present results in verbal and written communications internally, and in top‑tier academic venues.

What you’ll need

• Pursuing PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a related field.
• Proficiency in one or more general‑purpose programming languages: C++, Python, Java, or C#.
• Strong research background in combinatorial optimization, Robotics planning, multi‑robot systems, or machine learning.
• Publications at high‑impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, ICLR, RSS, ICRA, IROS, RAL, AAAI, ICAPS, IJCAI, JAIR, etc.) on some of the aforementioned topics.

Compensation and Benefits

The base range for this position in the posted location is $52.00 - $54.00 however, base pay offered may vary depending on job‑related knowledge, skills, and experience.

• transportation
• housing
• medical
• dental
• vision
• disability
• 401K
• PTO
• other benefits

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.

Equal Opportunity

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.