Applied Science Manager, Amazon Robotics

About the Role

Key Responsibilities

• Research, implement, deliver, and maintain critical computer vision and machine learning capabilities at Amazon Robotics.
• Motivate, reward, and coach a diverse team, recruiting and retaining top talent while managing day-to-day performance.
• Keep technical skills current to contribute to architecture and design discussions.
• Participate in deep-dive troubleshooting exercises and drive technical post-mortem discussions to identify root causes of complex issues.
• Set a vision for the team and create product roadmaps, prioritizing technical and product requirements.
• Guide the research, design, deployment, and evaluation of complex computer vision and ML algorithms for contact-rich, cluttered, real-world manipulation problems.
• Work closely with motion, hardware, and software teams to create integrated robotic solutions.
• Implement best practices in applied research and software development, managing project timelines, resources, and deliverables.

Requirements

• PhD, or Master's degree and 4+ years of industry or academic research experience.
• 6+ years of applied research experience.
• 3+ years of experience managing scientists or machine learning engineers.
• Experience building machine learning models or developing algorithms for business applications.
• Proficiency in programming in Java, C++, Python, or related languages.
• Knowledge of engineering practices and patterns for the full software/hardware/networks development lifecycle, including coding standards, code reviews, source control, build processes, testing, certification, and livesite operations.
• Strong understanding of computer vision and machine learning, including classical methods, deep neural networks, and foundation models.

Nice to Have

• Experience hiring and growing top talent.
• Familiarity with CV detection (segmentation, classification, performance KPIs such as mAP, ROC, Recall-at-set-precision).
• Knowledge of 3D geometry and camera calibrations.
• Experience with the latest developments in ML, such as foundation models, ViTs, contrastive loss, and generative models like diffusion models.

Qualifications

• Educational background including a PhD or Master's degree.

Benefits & Perks

• Medical, Dental, and Vision Coverage.
• Maternity and Parental Leave Options.
• Paid Time Off (PTO).
• 401(k) Plan.