Principal Solutions Architect Devices Bd Partner Products jobs at Amazon in United States, Sunnyvale

You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization.You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads.Key job responsibilities
You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically exceptional with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

- 5+ years of practical work applying ML to solve complex problems experience
- Graduate degree in with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science
- 7+ years of combined academic and research experience
- Strong publication record in top-tier journals and conferences
- Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements
- Experience programming in Java, C++, Python or related language
- Excellent written and spoken communication skills

- PhD with specialization in Artificial Intelligence, Natural Language Processing, Machine Learning, or Computational Cognitive Science
- 10+ years of combined academic and research experience
- First author research on scaling laws, evaluation metrics, data mixture optimization, data efficiency, or neural network architectures in top-tier journals and conferences
- Functional thought leader and sought after for key tech decisions
- Experience influencing decisions at an executive level
- Experience mentoring and training the research scientist community on complex technical issues
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Excellent written and spoken communication skills with successful delivery to customers

Key job responsibilities
As a Principal Applied Scientist, you will:
• Own the technical architecture and optimization strategy for ML models deployed across Amazon's device ecosystem, from existing to yet-to-be-shipped products.
• Develop novel model architectures optimized for our custom silicon, establishing new methodologies for model compression and quantization.
• Create an evaluation framework for model efficiency and implement multimodal optimization techniques that work across vision, language, and audio tasks.
• Define technical standards for model deployment and drive research initiatives in model efficiency to guide future silicon designs.
• Spend the majority of your time doing deep technical work - developing novel ML architectures, writing critical optimization code, and creating proof-of-concept implementations that demonstrate breakthrough efficiency gains.
• Influence architecture decisions impacting future silicon generations, establish standards for model optimization, and mentor others in advanced ML techniques.

This role requires a blend of expertise at the intersection of ML and hardware optimization. You must be an expert in model training, with deep knowledge of cutting-edge architectures for vision, language, and multimodal tasks. Crucially, you need to be a specialist in hardware-aware quantization, with hands-on experience in model compression techniques like pruning and distillation. A strong background in computer architecture and familiarity with ML accelerator designs is essential, as is expertise in efficient inference algorithms and low-precision arithmetic.
Basic Qualifications:
• Advanced degree (PhD preferred) in Computer Science, Electrical Engineering, or a related technical field
• 8+ years of experience in machine learning, with a focus on model architecture design, optimization, and deployment
• Expertise in developing and deploying deep learning models for real-world applications, including vision, language, and multimodal tasks
• Strong background in computer architecture, hardware acceleration, and efficient inference algorithms
• Hands-on experience with model compression techniques such as pruning, quantization, and distillation
• Proficiency with deep learning frameworks like TensorFlow, PyTorch, or ONNX

• PhD in Computer Science, Electrical Engineering, or a related technical field
• 10+ years of experience in machine learning, with a track record of developing novel model architectures and optimization techniques
• Proven expertise in co-designing ML models and hardware accelerators for efficient on-device inference
• In-depth understanding of the latest advancements in model compression, including techniques like knowledge distillation, network pruning, and hardware-aware quantization
• Experience working on resource-constrained embedded systems and deploying ML models on edge devices
• Demonstrated ability to influence technical strategy and mentor cross-functional teams
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical stakeholders

A Principal Applied Scientist will solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader; develop solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility; and tackle intrinsically hard problems acquiring expertise as needed.Principal Applied Scientists are expected to decompose complex problems into straightforward solutions. You will amplify your impact by leading scientific reviews within your organization or at your location; and scrutinize and review experimental design, modeling, verification and other research procedures. You will also probe assumptions, illuminate pitfalls, and foster shared understanding; align teams toward coherent strategies; and educate keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends.Key job responsibilities
You will be responsible for defining key research directions, inventing new machine learning techniques, conducting rigorous experiments, and ensuring that research is translated into practice. You will also develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them.A Principal Applied Scientist will participate in organizational planning, hiring, mentorship and leadership development. You will build scalable science and engineering solutions, and serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

- Graduate degree in Computer Science, Math, or related field.
- Experience in building complex, real-time systems involving AI, ML, and NLP with successful delivery to customers.
- Experience with project delivery for large, cross-functional projects with evolving requirements.

- PhD with specialization in Artificial Intelligence, Natural Language Processing, Machine Learning, or Computational Cognitive Science
- 10+ years of combined academic and research experience
- First author research on scaling laws, evaluation metrics, data mixture optimization, data efficiency, or neural network architectures in top-tier journals and conferences
- Functional thought leader and sought after for key tech decisions
- Experience influencing decisions at an executive level
- Experience mentoring and training the research scientist community on complex technical issues
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Excellent written and spoken communication skills with successful delivery to customers

- Lead the sourcing, selection, contract negotiation and management of one or more EMS suppliers in alignment with the overarching EMS strategy and within the Integrated Management System. Ensure a competitive sourcing environment leading to continuous improvement in Engr. Services, Line Readiness, Quality, Business Management, Contract management and adherence, delivery, cost and social responsibility.- Actively engage the Device Operations and Engineering organizations with the EMS suppliers on one or more products/product lines to achieve the programmatic objectives.This requires that the Business Manager be both an advocate for the supplier within Lab126 and be their harshest critic to ensure the best possible performance. Upon success, the Business Manager will instill a forward-thinking collaborative and mutually-beneficial long-term relationship with a holistic point of view, not just a product or single supplier perspective – a business owner. These high profile responsibilities require significant breadth and business acumen as the responsibilities are very diverse and impactful:Negotiation Skills – Lead all commercial discussions related to EMS relationships. Able to negotiate best in class contract pricing, terms and conditions on large contracts with suppliers who are exceptionally skilled at protecting thin margins. Exercise good judgement in knowing when and how best to address issues or drive change.

- 6+ years of developing, negotiating and executing business agreements experience
- 6+ years of professional or military experience
- Bachelor's degree
- Knowledge of publisher ad tech stacks and/or advertising technology
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience selling enterprise software or cloud-based applications
- Experience explaining complex technical concepts to various business and technical audiences
- Experience presenting to both technical and non-technical executive audiences

You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization.You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads.Key job responsibilities
You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

- 5+ years of hands-on work in predictive modeling and analysis experience
- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- Experience working in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python or related language
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment

- 10+ years of relevant work in industry or academia experience
- Knowledge of problem solving, algorithm design and complexity analysis
- Experience creating novel algorithms and advancing the state of the art
- Have peer-reviewed scientific contributions in premier journals and conferences

Key job responsibilities
What will you do?
• Analyze deep learning workloads and map them to Amazon’s Neural Edge Engine
• Propose and implement new hardware architectures or improvements to our existing ones, that enable future ML workloads to run efficiently on our accelerator
• Collaborate closely with compiler engineers, model developers, hardware architects and product teams to build the best ML centric hardware and software solutions for our devices
• Deliver hardware architecture, microarchitecture and other design collateral for our next generation ML accelerators
• Build tools for modeling and performance evaluation to enable power, performance, cost options and trade offs
• Work with full stack silicon designers to realize the architecture on silicon.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

We are seeking a Sr. Manager, Applied Science to lead and build our science team focused on machine learning applications in life sciences. The role combines scientific leadership with people management responsibilities to drive innovative solutions. The role requires balancing exploratory research with delivering production-ready solutions while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications.
Key job responsibilities
- Lead ML for life science efforts using computational design approaches and ML-based tools.- Transform complex real world problems into scientific challenges and allocate resources effectively.
- Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs.
- Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor.

- Deep expertise in machine learning, with broad knowledge across biology and life science.
- Experience managing technical teams.
- Strong understanding of scientific methodologies and experimental design.
- Ability to guide teams in developing production-level code and systems.
- Track record of leading cross-functional scientific teams and fostering collaboration.
- 10+ years as a scientist or science manager.
- PhD in computer science, computational biology or relevant field .

- Experience with deep learning frameworks (PyTorch, TensorFlow).
- Familiarity with high-performance computing environments.
- Experience with molecular modeling software and structural biology tools.
- 5+ years of management experience.