Sr Applied Scientist, Last Mile Delivery Automation
Job Description
As a Senior Applied Scientist for Last Hundred Yards Automation, you will be at the forefront of developing cutting-edge AI and ML solutions that power our autonomous delivery robots. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world autonomous navigation, obstacle detection, and dynamic path planning. You will work closely with robotics engineers, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient last-yard delivery operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments.Key job responsibilitiesThe Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems.About the teamLMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.
Locations
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building machine learning models for business application experienceintermediate
- - PhD, or Master's degree and 6+ years of applied research experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- - 3+ years of building machine learning models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)
Responsibilities
- The Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems.
- About the team
- LMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.
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Sr Applied Scientist, Last Mile Delivery Automation
Job Description
As a Senior Applied Scientist for Last Hundred Yards Automation, you will be at the forefront of developing cutting-edge AI and ML solutions that power our autonomous delivery robots. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world autonomous navigation, obstacle detection, and dynamic path planning. You will work closely with robotics engineers, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient last-yard delivery operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments.Key job responsibilitiesThe Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems.About the teamLMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.
Locations
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building machine learning models for business application experienceintermediate
- - PhD, or Master's degree and 6+ years of applied research experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- - 3+ years of building machine learning models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)
Responsibilities
- The Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems.
- About the team
- LMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.