Amazon Machine Learning Engineer Data WWPS US Federal 

United States, Texas, Arlington 

802089328

In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have deep expertise in NLP/NLU, generative AI, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI.Key job responsibilities
As a Machine Learning Engineer, you are proficient in developing and deploying advanced ML models to solve diverse challenges and opportunities. You will be working alongside scientists to develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) approaches to areas within the natural language processing and understanding spaces including GenAI, document processing and understanding, call center analytics, and chat experiences.The primary responsibilities of this role are to:Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 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
- 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models
- Experience using Python and frameworks such as Pytorch, TensorFlow

- Experience leading the design, development and deployment of business software at scale or recent hands-on technology infrastructure, network, compute, storage, and virtualization experience
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field
- Practical experience in solving complex problems in an applied environment
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
- Experiences related to machine learning, deep learning, NLP, GenAI, distributed training, model hosting,etc