Software Development Manager Agi Info - Web Information Systems jobs at Amazon in United States, Sunnyvale

As a Battery System Engineer, you will engage with an experienced cross-disciplinary staff to conceive, and design innovative consumer product. You will work closely with an internal interdisciplinary team, and outside partners to drive key aspects of product definition and execution. You must be responsive, flexible, and able to succeed within an open collaborative peer environment.Key job responsibilities
In this role, you will:
1. Lead the design, development, and delivery of Li-ion battery system per performance and safety requirements
2. Drive battery development from NPI through mass production
3. Research and evaluate emerging battery technologies5. Design battery protection circuit and pack design for NPI programs include schematic design, and component selection.
6. Develop and review battery pack schematics, BOMs and layout to meet design requirements
7. Conduct system and design reviews, failure mode and effects analysis (DFMEA), and risk assessments
8. Analyze and resolve battery-related issues in production and field
9. Perform battery safety assessment and design for safety
10. Support battery certification processes (CTIA/IEEE1725)

- Bachelor's degree in electrical engineering or equivalent
- Experience in developing functional specifications, design verification plans and functional test procedures
- 5+ years of experience with battery technology development
- Experience with designing and qualifying battery components

- Master's degree in Electrical Engineering, Chemistry or equivalent preferred
- Strong EE fundamentals in electronic circuit design/development with microcontroller-based embedded systems.
- 5+ years experience with battery cell chemistry and platform design
- 5+ years experience with battery protection and management systems including protection ICs, Chargers, and Fuel gauge
- 5+ years of experience with battery product development in high volume consumer battery e.g. Cell phone/Tablet/E-reader/wearables.
- Knowledge of embedded software/firmware integration

Come join us to accelerate deep learning networks on Az1/Az2/Az3 Neural Edge processors and beyond. We deliver solutions to offload Speech, Computer Vision and Generative AI workloads on a range of devices from Blink Smart Home camera to Echo Show line of products.In this role you will lead a team working alongside partner science teams to develop the compiler infrastructure and lower deep learning workloads to heterogeneous device backends. You will also drive partnerships with peer science teams to innovate on model quantization and compression techniques for efficient execution on hardware, ensuring scalability across current and future generations of ML accelerator architectures.
Key job responsibilities· Drive technical vision and strategy for the deep learning compiler stack
·. Manage project planning, execution, and delivery of compiler solutions
· Build and maintain strong partnerships with hardware, software, applied science and product teams
·. Develop and mentor team members, manage performance, and drive career growth
· Drive hiring and team building initiatives
· Architect and oversee development of software stack for deep learning accelerator
· Lead design reviews, API development, and documentation efforts
· Ensure successful delivery of deep learning workloads on heterogeneous device backends

- 3+ years of engineering team management experience
- 7+ years of working directly within engineering teams experience
- 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- 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
- Experience partnering with product or program management teams
- Experience with neural network inference offload to GPU, DSP or custom accelerators

- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers
- 7+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
- Experience building and leading compiler development teams
- Experience managing teams working on application specific accelerators or custom instruction sets

Key job responsibilities
• Provide Infrastructure support of incoming system tickets, including extensive troubleshooting tasks, with responsibilities covering multiple products, features and services.
• Work on maintenance driven coding projects, primarily in Java and AWS technologies.
• Software deployment support in staging and production environments.
• Develop tools to aid operations and maintenance.
• System and Support status reporting.
• Ownership of one or more Digital products or components.
• Improve the infrastructure, operational performance, and stability.
• Participate in designs, code and procedures reviews.
• Identify opportunities arising from technical discussions and do the technical trade-offs.
• Troubleshoot, research root causes thoroughly resolve defects.
• Drive Company Wide Campaigns with Support and Engineering teams and drive it to closure.
• Keep the compliance risks for internal systems under control.
• Drive large scale projects such as migration to native, pipeline automation and drive it to closure.

- Experience in automating, deploying, and supporting infrastructure
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- Experience with Linux/Unix

- Experience with CI/CD pipelines build processes

Key job responsibilities
• Develop high-performance inference software for a diverse set of neural models, typically in C/C++
• Design, prototype, and evaluate new inference engines and optimization techniques
• Participate in deep-dive analysis and profiling of production code
• Optimize inference performance across various platforms (on-device, cloud-based CPU, GPU, proprietary ASICs)
• Collaborate closely with research scientists to bring next-generation neural models to life
• Partner with internal and external hardware teams to maximize platform utilization
• Work in an Agile environment to deliver high-quality software against tight schedules
• Hold a high bar for technical excellence within the team and across the organization

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Bachelor's degree in Computer Science, Computer Engineering, or related fields
- Experience programming with at least one software programming language, or experience in embedded development in C/C++
- Master's degree, or a PhD and experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience with portable device hardware architectures
- Experience working effectively across cross-functional teams and partnering well with people at all levels within an organization
- Experience creating novel algorithms and advancing the state of the art
- Experience with inference frameworks such as PyTorch, TensorFlow, ONNXRuntime, TensorRT, LLaMA.cpp, etc.
- Proficiency in performance optimization for CPU, GPU, or AI hardware
- Proficiency in kernel programming for accelerated hardware using programming models such as (but not limited to) CUDA, OpenMP, OpenCL, Vulkan, and Metal
- Experience with latency-sensitive optimizations and real-time inference
- Knowledge of model compression techniques (quantization, pruning, distillation, etc.)
- Experience with LLM efficiency techniques like speculative decoding and long context

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

Work hard. Have fun. Make history.We are looking for an Embedded Software Development Engineer to help design, develop, and integrate our next generation devices. In this role you will work with customers, system architects, program managers and hardware engineers to implement, troubleshoot, fix kernel drivers, BSP for our next generation devices.
You will be responsible for the development of real-time embedded firmware and embedded Linux software that implements security controls for the platform.
Key job responsibilities
- Design, build, and maintain efficient, reusable C code for multimedia BSP
- Debug and troubleshoot kernel drivers and multimedia framework integration
- Develop and customize multimedia Board Support Package (BSP) and graphics
- Implement low-level embedded software for multimedia device platforms
- Develop and test software layers within Linux Kernel multimedia frameworks
- Optimize multimedia performance and resolve system integration challenges
- Maintain code quality and technical documentation for multimedia components
- Provide technical guidance on embedded multimedia software development
- Participate in multimedia-focused code and design reviews

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Embedded C/Linux development experience

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Linux driver and kernel development
- Experience with assembly language development

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.In this role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale solutions for never-before-solved problems.Key job responsibilities
1. Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimization
2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker
3. Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams5. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
6. Influence customer AI strategy through technical expertise and industry insights8. Provide thought leadership in internal and external engagements
9. Support pre-sales activities to provide technical expertise and review project scoping and risksAbout the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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

- Strong experience in building large scale machine learning or deep learning models and in Generative AI model development
- Experience in data and machine learning engineering and cloud native technologies
- Strong experience communicating across technical and non-technical audiences
- Strong experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation

- Master's degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science
- Knowledge of the primary AWS services (ec2, elb, rds, route53 & s3)
- Experience with software development life cycle (sdlc) and agile/iterative methodologies
- Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet