Amazon Machine Learning Engineer Sponsored Product Demand Utilization 

United States, California, Palo Alto 

476832276

About the Role
About the OrgRealtime systems within our org operate with tight 10s of milliseconds, and high throughput requirements for offline systems, resulting in high impact from performance optimization.Key job responsibilities* Serve as a tech lead for defining innovative and cutting edge ML infrastructure for both inference and training
* Build POCs and infrastructure for deploying and supporting models in production. Own A/B testing of experiments using this infrastructure
* Work closely with scientists across the org to understand requirements and impact opportunities
* Work closely with product managers to contribute to our mission, and proactively identify opportunities where cutting edge ML Infra can help improve customer experience
* Stay on top of modern ML Infra and ML Ops technologies to understand where they can provide the most value within the org
* Help attract and recruit technical talent, mentor engineers and scientists in the team
* Vertical integration with science and engineering, with opportunities to touch all aspects of the model lifecycle, through training, optimization and inference
* Exposure to bleeding edge model optimization techniques for LLMs and other large models, with clear path to revenue impact from optimization. This is a rare opportunity across the industry to gain experience and drive exploration in techniques like quantization, sparsity, knowledge distillation and neural architecture search on large scale models in an enterprise setting.
* Challenging technical space, where we care about fitting inference for the largest possible models within tight realtime constraints (10s of ms) and high performance of numerical systems is mission critical.
* Large scale impact on revenue through delivery of bar-raising optimizations and solutions for teams across the org.
* Latitude to innovate on greenfield projects, this is effectively an R&D role with the intention of innovating on existing legacy systems.BASIC QUALIFICATIONS* 3+ years of non-internship professional software development experience
* 3+ years of programming with at least one software programming language experience
* 3+ 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
* Experience with common machine learning techniques such as pre-processing data, training, and evaluation
* Experience in building large-scale machine-learning MLOps infrastructure for inference, eval or other parts of the model lifecyclePREFERRED QUALIFICATIONS* 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
* Industry experience in software development.
* Experience with production machine learning systems
* Experience profiling and identifying performance bottlenecks on CPU, GPU or other accelerators (e.g. using nsys, torchprof, VTune, gprof etc...)
* Excellent distributed systems (e.g. AWS or other cloud infra) design experience
* Experience with ML libraries/frameworks such as PyTorch, JAX, Tensorflow, Keras etc...
* Experience with MLOps tooling like MLFlow, Sagemaker, Kubeflow, DVC etc...
* Experience with systems programming, and low level optimization in Rust, C++, C or other similar languages.
* Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing
* Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices

- 3+ years of non-internship professional software development experience
- 3+ 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

- 5+ 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