The OTS DataTech team drives enterprise data strategy and support across OTS. Our charter encompasses OTS-wide efforts, including Data as a Product (DaaP), enterprise data infrastructure, AI/ML capability, and supporting specific business-critical programs, fueling innovation and automation for OTS.
We are looking for a passionate, talented, and innovative Applied Scientist with a background in developing and implementing state-of-the-art machine learning solutions within the realms of supervised and unsupervised learning, Generative AI (GenAI), and optimization.
Key job responsibilities
In this role, you will play a pivotal role in shaping the vision, roadmap, design, development, and implementation of science based solutions from beginning to end.
- You will contribute to building and maintaining an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases. You will be responsible for the seamless integration of scientific products with existing systems, ultimately leading to increased operational efficiency and productivity across OTS.
- You will also have the opportunity to leverage our foundational GenAI platform to help OTS customers build GenAI applications for their use cases.
- You will be closely partnering with a cross-functional team of stakeholders including with Applied Scientists, Data Scientists, Machine Learning Engineers, Data Engineers, Product Managers, and Technical Program Managers.
Come join OTS DataTech as we continue to innovate and pioneer the AI/ML space within OTS!
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
BASIC QUALIFICATIONS
- MS or PhD in quantitative field (CS, CE, ML preferred) or equivalent relevant work Strong background in machine learning, including supervised and unsupervised learning algorithms.
- Experience developing, building and implementing complex software systems, especially involving ML, that have been successfully delivered to customers.
- Knowledge of Generative AI and its applications.
- Proficiency in programming languages such as Python, Java, or C++.
- Strong communication skills, both written and verbal.
PREFERRED QUALIFICATIONS
- Experience with fine-tuning and deploying Large Language Models (LLMs) for customer facing GenAI applications.
- 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).
- Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain).
- Experience with big data technologies (e.g., Hadoop, Spark).
- Knowledge of RAG and its applications.
- Experience with AWS technologies.
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.