Applied Scientist, Generative Artificial Intelligence (AI) Innovation Center

DESCRIPTIONThe Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms.As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We're looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.Key job responsibilities
- Collaborate with scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges
- Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
- Provide customer and market feedback to Product and Engineering teams to help define product direction.A day in the life
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 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 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.About the team
Work/Life Balance
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.Employee Benefits
We're passionate about supporting the needs of our people and their family. This may include:- Comprehensive Private Health Insurance
- Paid Maternity and Parental Leave
- Amazon Employee Discount on product and services
- Salary Continuance and Life InsuranceWhat if I don't meet all the requirements?That's okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You'll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.We are open to hiring candidates to work out of one of the following locations:Melbourne, VIC, AUSBASIC QUALIFICATIONS- 2+ years of building machine learning models or developing algorithms for business application experience
- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)PREFERRED QUALIFICATIONS- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Working knowledge of generative AI and hands on experience in prompt engineering, deploying and hosting Large Foundational Models
- Hands on experience building models with deep learning frameworks like Tensorflow, PyTorch, or MXNetAcknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.IDE statement:
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, disability, age, or other legally protected attributes.