Machine Learning Engineer, Data and Machine Learning, WWPS US Federal
DESCRIPTION
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? Amazon Web Services (AWS) Professional Services (ProServe) is looking for Machine Learning Engineers who like helping U.S. Federal agencies implement innovative cloud computing solutions and solve technical problems using state-of-the-art language models in the cloud. AWS ProServe engages in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about strong success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.
At AWS, we're hiring experienced Machine Learning Engineers with a background in NLP, generative AI, and document processing to help our customers understand, plan, and implement best practices around leveraging these technologies within their AWS cloud environments. Our consultants deliver proof-of-concept projects, reusable artifacts, reference architectures, and lead implementation projects to assist organizations in harnessing the power of their data and unlocking the potential of advanced NLP and AI capabilities.
In this role, you will work closely with national security 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.
It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed.
This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.
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:
- Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them
- Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithms
About the team
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
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.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
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.
BASIC QUALIFICATIONS
- 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
- Current, active US Government Security Clearance of TS/SCI with Polygraph
PREFERRED QUALIFICATIONS
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field
- experience using Python and frameworks such as Pytorch, TensorFlow
- 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
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.