DESCRIPTION The Sensory Inference team at AGI is a group of innovative developers working on groundbreaking multi-modal inference solutions that revolutionize how AI systems perceive and interact with the world. We push the limits of inference performance to provide the best possible experience for our users across a wide range of applications and devices. We are looking for talented, passionate, and dedicated Inference Engineers to join our team and build innovative, mission-critical, high-volume production systems that will shape the future of AI. You will have an enormous opportunity to make an impact on the design, architecture, and implementation of cutting-edge technologies used every day, potentially by people you know. This role offers the exciting chance to work in a highly technical domain at the boundary between fundamental AI research and production engineering. 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 aggressive schedules * Hold a high bar for technical excellence within the team and across the organization BASIC QUALIFICATIONS * 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 * Strong C/C++ programming skills * Solid understanding of deep learning architectures (CNNs, RNNs, Transformers, etc.) PREFERRED QUALIFICATIONS * 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 * Experience with inference frameworks such as PyTorch, TensorFlow, ONNXRuntime, TensorRT, LLaMA.cpp, etc. * Proficiency in performance optimization for CPU, GPU, or AI hardware * Experience with latency-sensitive optimizations and real-time inference * Understanding of resource constraints on mobile/edge hardware * Knowledge of model compression techniques (quantization, pruning, distillation, etc.) * Strong communication skills and ability to work in a collaborative environment * Passion for solving complex problems and driving innovation in AI technology Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.