Machine Learning Engineer, Professional Services

Do you love breaking down problems to develop machine learning (ML) products that impact millions of people worldwide? Do you relish the opportunity to identify, define, and build ML software solutions that revolutionize the way businesses function? The Global Practice Organization in Professional Services at Amazon Web Services (AWS) is in search of a Software Development Engineer II to construct, deliver, and maintain complex ML products that captivate our customers and enhance our performance. You will engineer fault-tolerant systems that operate at an immense scale as we consistently innovate top-tier services and applications in the AWS Cloud. Main Job Responsibilities: Our ML Engineers work collaboratively across various teams, projects, and environments to directly impact our worldwide customer base. You will bring a passion for the fusion of software development with AI and machine learning. Your responsibilities will also include: - Solving complex technical problems, often ones never solved before, across all layers of the stack. - Designing, implementing, testing, deploying, and maintaining innovative ML solutions to enhance service performance, durability, cost, and security. - Constructing high-quality, highly available, always-on products. - Researching implementations that provide the best experiences for customers. A Day in the Life: In your day-to-day role, you'll devise and code solutions to help our team streamline efficiencies in ML architecture, create metrics, implement automation and other improvements, and identify the root cause of software defects. You'll also: - Build high-impact ML solutions for our broad customer base. - Engage in design discussions, code reviews, and communication with internal and external stakeholders. - Collaborate cross-functionally to aid in driving business solutions with your technical input. - Work in a startup-like development environment, always focusing on the most crucial tasks. About the Team: The Global Practice Organization for Analytics is a team within the AWS Professional Services Organization. Our mission is to be the frontrunners in defining machine learning strategy and ensuring the scale of Professional Services' delivery. We strategize on initiatives, provide domain expertise, and control the development of high-quality, repeatable offerings that expedite customer outcomes. Inclusive Team Culture: At AWS, we value our differences. We are committed to enhancing our culture of inclusion. We have thirteen employee-led affinity groups, reaching 85,000 employees in over 190 chapters globally. We offer innovative benefits and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s inclusive culture is underpinned by our 16 Leadership Principles, which remind team members to seek diverse perspectives, be curious and learn, and earn trust. Work/Life Balance: Our team highly values work-life harmony. Striking a healthy balance between your personal and professional life is key to your happiness and success here. We are a customer-obsessed organization—leaders start with the customer and work backward. They strive exhaustively to gain and retain customer trust. As such, this is a customer-facing role in a hybrid delivery model. Projects may include remote delivery methods and on-site engagement, including travel to customer locations as required. Mentorship & Career Growth: Our team is committed to supporting new members. We have a wide mix of experience levels and tenures, and we are fostering an environment that celebrates knowledge sharing and mentorship. We care about your career growth and aim to assign projects that will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. This is a customer-facing role, and you may be required to travel to client locations and provide professional services as needed. We are open to hiring candidates to work in the following locations: Atlanta, GA, USA | Austin, TX, USA | Boston, MA, USA | Chicago, IL, USA | Herndon, VA, USA | Minneapolis, MN, USA | New York, NC, USA | San Diego, CA, USA | San Francisco, CA, USA | Seattle, WA, USA Basic Qualifications: - 2+ years of data scientist experience - 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.) - 3+ years of experience with machine learning/statistical modeling data analysis tools and techniques, and the parameters that influence their performance - Experience applying theoretical models in a practical environment Preferred Qualifications: - Experience in a scripting language such as Python or Perl - History in an ML or data scientist role with a large technology company Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate based on 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. In accordance with the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.