Applied Scientist: Fleet Scheduling & Optimization

Amazon; North Reading (MA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon Robotics is seeking an Applied Scientist to research and develop state-of-the-art algorithms and software that manage fleets of autonomous robots. You will tackle scheduling and optimization challenges to improve task completion efficiency across fulfillment and transportation networks.

You will collaborate with a world-class team of scientists and engineers, mentor peers, and influence long-term strategy and roadmaps while delivering impactful, scalable solutions in a fast-paced

Qualifications

• PhD or Master’s degree in engineering, science, technology, CS, mathematics or related field.
• 1+ years programming in Java, C++, Python or related language.
• Experience in optimization or scheduling for fleets of mobile robots.
• Experience building ML models or algorithms for business applications.

Responsibilities

• Architect, design, and implement robotic applications and infrastructure.
• Influence team strategy and contribute to long-term roadmaps.
• Collaborate with stakeholders to iterate on design and implementation.
• Maintain high standards with reviews, fault tolerance, and operational excellence.
• Prototype and test concepts via simulation, emulators, and live robotics.
• Test prototypes with customers/partners and incorporate feedback.
• Mentor other engineers on the team.

Skills

Programming languages

Optimization algorithms

Machine learning

Algorithms

Team collaboration

Education

PhD or Master’s degree

Related quantitative field

Job description

Amazon Robotics is seeking an Applied Scientist to research and develop state-of-the-art algorithms and software that manage fleets of autonomous robots. You will tackle scheduling and optimization challenges to improve task completion efficiency across fulfillment and transportation networks.

You will collaborate with a world-class team of scientists and engineers, mentor peers, and influence long-term strategy and roadmaps while delivering impactful, scalable solutions in a fast-paced