Principal Tpm - Cloudtune 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

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

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.

Key job responsibilitiesAbout the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
- Experience in building quantitative solutions as a scientist or science manager
- Experience directly managing scientists or machine learning engineers
- Experience in applying statistical models for large-scale application and building automated analytical systems

- Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
- Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
- Bachelor's degree in Computer Science or equivalent

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).

PhD with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science 10+ years of combined academic and research experience. Strong publication record in top-tier journals and conferences. Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. Mentors and trains the research scientist community on complex technical issues. Experience developing software in traditional programming languages (C++, Java, etc..). Excellent written and spoken communication skills