Machine Learning Engineer, Public Sector - AWS Professional Services

Job summary
Are you excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Do you to help public sector, medical center, and non-profit customers derive business value through the adoption of Artificial Intelligence (AI)? Are you to learn from many different enterprise’s use cases of AWS ML and DL? Are you thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?

At Amazon Web Services (AWS), we are helping large enterprises build ML and DL models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML or DL models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.

Please feel free to apply regardless of location noted on this job. Our Data Scientists can live in any location where we have a WWPS Professional Service office.

We’re looking for top architects, system and software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for new and intriguing problems.

The primary responsibilities of this role are to:

• Design data architectures and data lakes
• Provide expertise in the development of ETL solutions on AWS
• Use ML tools, such as Amazon SageMaker Ground Truth (GT) to annotate data. Work with Professional Services on designing workflow and user interface for GT annotation.
• Collaborate with our data scientists to create scalable ML solutions for business problems
• Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
• Analyze and extract relevant information from large amounts of historical data — provide hands-on data wrangling expertise
• Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms
• This position can have periods of up to 10% travel.

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

We're dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.

Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.

Basic Qualifications

• BS in computer science, or related technical, math, or scientific field
• 3+ years of relevant experience in building large scale enterprise IT systems
• 3+ year of experience with data engineering, ETL, and data wrangling
• 1+ year of public cloud computing experience in AWS

Preferred Qualifications

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• Working knowledge of deep learning, machine learning and statistics.
• User interface experience with Javascript, HTML
• Model deployment experience using C++
• Knowledge of ETL tools and databases (both SQL-based, NoSQL)
• Experience in using Python, R or Matlab or other statistical/machine learning software
• Strong communication and data presentation skills
• The motivation to achieve results in a fast-paced environment.
• Comfortable working in a fast paced, highly collaborative, dynamic work environment

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.



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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.