Amazon Sr Machine Learning Scientist OTS DataTech AI 

United States, Texas, Austin 

984382676

We are looking for a passionate, talented, innovative, experienced and Senior Machine Learning Scientist with a background in building cutting-edge scientific and engineering components that are highly scalable, extensible, and robust to enable exponential growth and adoption of AI/ML within OTS. In this role, you will play a pivotal role in shaping the vision, roadmap, and execution of science and engineering-based solutions from beginning to end.You will build foundational GenAI components that will enable our customers to build GenAI applications for their use cases across OTS. You will enable the seamless integration of scientific products with new and existing systems, ultimately leading to increased operational efficiency and productivity across OTS. You will also work on projects involving supervised and unsupervised learning, NLP, and more. You will be responsible to build and maintain an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases within the realms of GenAI, supervised and unsupervised learning, optimization, and more.You will evangelize the adoption of our scientific solutions across the organization. You will be closely partnering with a cross-functional team of stakeholders including with Applied Scientists, Data Scientists, Data Engineers, Product Managers, and Technical Program Managers.As part of other initiatives, you will also contribute to building a data infrastructure that supports our DataMesh framework, enabling engineering and BI self-service architecture for DaaP, 3P software integrations, and more.Key job responsibilities
* Build and maintain an MLOps Platform that supports end-to-end AI/ML operations.
* Shape the vision and roadmap for AI/ML across the organization, leading their research and development from concept to deployment from an engineering perspective.
* Guide teams to adopt software engineering best practices that uplift our Operational Excellence standards.
* Promote and facilitate the adoption of AI/ML solutions across the organization.
* Build and maintain data infrastructure that supports the DataMesh framework and enables self-service architecture.A day in the life- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of industry or academic research experience
- 5+ years of applied research experience
- 5+ years of building machine learning models or developing algorithms for business application experience
- 5+ years of industry or academic research experience
- Experience programming in Java, C++, Python or related language
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

- 5+ years of experience in full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience developing, building and implementing complex software systems and machine learning systems that have been successfully delivered to customers.
- Experience developing, building, and implementing data engineering pipelines and infrastructure.
- Experience with AWS technologies.
- Experience with MLOps tools and frameworks (e.g., SageMaker, MLflow).
- Background in AI/ML, including GenAI, supervised and unsupervised learning, and optimization algorithms.
- Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain).
- Publications at top-tier peer-reviewed conferences or journals.