Applied Science Manager - Perception, Amazon Robotics

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, not invent. Remove boilerplate, navigation, legal, EEO, scam warning, duplicated lines, application instructions. We need to parse the description. Key parts: - Intro paragraph: "Do you want to create intelligent, adaptable robots with global impact? The Vulcan Stow team ... builds high-performance, real-time robotic systems ..." This is description about role. Could go under About the role. - "Key job responsibilities" list: People Leadership, Technical Vision, Cross-functional Collaboration, Delivery Excellence, Problem Solving. Each with bullet points. - "A day in the life" repeats some of responsibilities; but we can treat as part of responsibilities or maybe separate? It's basically same content; we can include under Responsibilities but avoid duplication. - Benefits: "Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: Medical, Dental, and Vision Coverage Maternity and Parental Leave Options Paid Time Off (PTO) 401(k) Plan" Later: "Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave." We need to preserve all substantive info; we can combine benefits into a list. - Pay: "The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually" Thus we have Pay section with salary range and mention of sign-on payments and RSUs. - Schedule: Not mentioned explicitly. There's no schedule info. So we should not create Schedule section. - Requirements / Qualifications / Skills: The posting includes "Basic Qualifications" and "Preferred Qualifications". Also maybe "Skills" could be derived from qualifications. We need sections: Requirements, Qualifications, Skills. We need to decide what to put where. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content. We have Basic Qualifications list: PhD, or Master's degree and 4+ years of industry or academic research experience; 6+ years of applied research experience; 3+ years of scientists or machine learning engineers management experience; Experience building machine learning models or developing algorithms for business application; Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet; Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals; Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations. Preferred Qualifications: Experience hiring and growing top talent; Deep expertise in 3D perception architectures - including encoder-decoder networks, vision transformers, multi-view reconstruction, point cloud processing and generative 3D models for scene completion. We could treat Basic Qualifications as Requirements, Preferred Qualifications as Qualifications, and maybe Skills could be derived from both (like deep learning libraries, 3D perception architectures, etc). But we must not invent or summarize away detail. We need to preserve ALL substantive information. If we create a Skills section, we must ensure it contains real specific content from posting. The posting does not have a separate "Skills" heading, but we could extract skills from qualifications (like experience with PyTorch, TensorFlow, MxNet; knowledge of engineering practices; deep expertise in 3D perception architectures). However that would be duplicating content already in Requirements/Qualifications. The instruction says: Prefer a few substantive sections over many thin ones. So maybe we combine Requirements and Qualifications into one section? But headings are prescribed; we can omit sections if no real specific content. We could put all qualification info under "Requirements" and leave Qualifications empty (omit). Or we could put Basic under Requirements, Preferred under Qualifications, and maybe Skills omitted. That seems reasonable: we have real content for Requirements and Qualifications. Skills section would be empty -> omit. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. Check if any other sections like "Skills" have content: maybe we could list specific skills like "Transformer-based architectures, generative 3D models, scalable data pipelines, sub-250ms perception outputs, encoder-decoder networks, query-based transformers, generative architectures". Those appear in responsibilities/description. But those are more like technical vision. Could be considered skills. However to avoid thin sections, we might incorporate them into Responsibilities or About the role. Since we already have Responsibilities covering technical vision, we can keep Skills omitted. Now we need to format. - About the role: combine introductory paragraphs and maybe "About The Team" video link? The "About The Team" includes a link to video. That's substantive info about team. Should we include? It's not boilerplate; it's about the team. Could be part of About the role. We'll include a paragraph describing the team and maybe the link as an tag? The instruction says output only HTML fragment; we can include for link. It's not prohibited. We'll preserve the link. Thus About the role content:

Do you want to create intelligent, adaptable robots with global impact? The Vulcan Stow team (https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem) at Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. We invent and deploy machine learning, optimization algorithms, and geometric reasoning models that empower robots to identify the best available placement opportunities, learn effective stow strategies, and continuously improve capacity utilization. Our mission is to deliver robust, real-time 3D scene understanding that drives downstream manipulation decisions - spanning semantic occupancy prediction, multi-view 3D reconstruction, depth estimation, and panoptic segmentation. We hire and develop subject matter experts in 3D computer vision, deep learning, and generative modeling, targeting high-impact algorithmic unlocks in scene completion, shape reasoning, and edge-optimized inference. We are seeking an experienced Applied Science Manager to lead the Perception team - a group of applied scientists and engineers pushing the frontier of 3D computer vision for robotics. You will drive technical vision using transformer-based architectures, generative 3D models, and scalable data pipelines to deliver sub-250ms perception outputs with the accuracy, robustness, and latency that production robots demand. Collaborating with cross-functional teams across match & affordances, motion planning, and fulfillment operations, you will ship models that run on real robots in real fulfillment centers.

Maybe also include the "About The Team" video link again? Already included. Now Responsibilities: we need

• for each responsibility. The responsibilities list includes People Leadership, Technical Vision, Cross-functional Collaboration, Delivery Excellence, Problem Solving. Each has sub-bullets. We can make each top-level responsibility as
• containing maybe a heading? But we just need list items; we can include the description inside
• . Could also nest
  for subpoints but not required. We'll keep simple: each
  • contains the heading and description. Thus:
    • People Leadership: Prioritize being a great people manager - motivating, rewarding, and coaching your diverse team is the most important part of this role. Recruit and retain top talent in 3D computer vision, deep learning, and perception systems. Excel in day-to-day people and performance management tasks.
    • Technical Vision: Set a vision for your team and create technical roadmaps focused on 3D scene understanding, semantic occupancy prediction, depth estimation, and multi-view fusion. Guide research, design, deployment, and evaluation of perception models - including encoder-decoder networks, query-based transformers, and generative architectures - that produce actionable 3D representations for downstream robot decision-making.
    • Cross-functional Collaboration: Work closely with match & affordances, motion planning, hardware, and fulfillment teams to deliver integrated perception solutions that are robust to occlusion, clutter, and sensor noise. Partner with ML infrastructure teams on scalable training pipelines, pseudo-ground-truth data generation, and edge deployment optimization.
    • Delivery Excellence: Implement best practices in applied research and software development. Manage project timelines, resources, and deliverables effectively. Keep technical skills current to contribute meaningfully to architecture decisions, model reviews, and inference optimization discussions.
    • Problem Solving: Regularly participate in deep-dive troubleshooting exercises and drive technical post-mortem discussions to identify root causes of perception regressions, model failures, depth/segmentation misalignments, and latency degradations.
    We could also include the "A day in the life" paragraph but it's duplicate; we can omit to avoid duplication. Now Requirements: Basic Qualifications list. We'll make
    • each. Thus:
      • PhD, or Master's degree and 4+ years of industry or academic research experience
      • 6+ years of applied research experience
      • 3+ years of scientists or machine learning engineers management experience
      • Experience building machine learning models or developing algorithms for business application
      • Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
      • Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
      • Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
      Now Qualifications: Preferred Qualifications list.
      • Experience hiring and growing top talent
      • Deep expertise in 3D perception architectures - including encoder-decoder networks, vision transformers, multi-view reconstruction, point cloud processing and generative 3D models for scene completion
      Now Benefits: combine both benefit paragraphs. We need to list benefits as
      • . The first paragraph: Medical, Dental, and Vision Coverage; Maternity and Parental Leave Options; Paid Time Off (PTO); 401(k) Plan. Also note that benefits can vary by location etc. We'll include that as a sentence maybe in

        then list. Second paragraph: Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. We can combine into a list avoiding duplication. Let's extract distinct benefits: - Medical coverage - Dental coverage - Vision coverage - Prescription coverage (mentioned in second) - Basic Life & AD&D insurance - Supplemental life plans (option) - EAP (Employee