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Amazon Sr Machine Learning Engineer SDE OTS DataTech 
United States, Texas, Austin 
390362915

16.09.2024
DESCRIPTION

We are looking for a passionate, talented, and innovative Sr. Machine Learning Engineer with a background in building cutting-edge infrastructure components and platforms 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 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. The MLOps Platform will streamline and standardize the entire Machine Learning Development Lifecycle including data processing, model training, deployment, and monitoring. You will evangelize the adoption of our solutions across the organization to help OTS builder teams quickly develop and deploy reliable AI/ML solutions in scale.By leveraging your deep technical expertise in machine learning and software engineering, you will help the DataTech team adopt engineering best practices and uplift our Operational Excellence standards.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 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

BASIC QUALIFICATIONS

- 5+ years of non-internship professional software development experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of programming with at least one software programming language experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of professional software development experience with CI/CD experience
- Bachelors or MS degree in computer science or engineering field (CE, EE, ML preferred)
- Strong communication skills, both written and verbal.


PREFERRED QUALIFICATIONS

- 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 Infrastructure as Code (IaC) and AWS Cloud Development Kit (CDK).
- Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, Airflow)
- 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).
- Experience with big data technologies (e.g., Hadoop, Spark).
- Experience as a mentor, tech lead, or leading an engineering team.