Sr. Applied Scientist, Science and Machine Learning, Project Kuiper Full-time

Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband network connectivity to unserved and underserved communities around the world.

Key job responsibilities

The Kuiper SMART team is a team of Machine Learning Engineers, Scientists, and Data Engineers that is working with stakeholders across Kuiper to solve ML and AI problems.

We are looking for a passionate, talented, and inventive Applied Scientist with a background in AI, Gen AI, Machine Learning, NLP, to lead delivering best in class automated customer service and business analytic solutions for our partner, the Kuiper Customer Service team. As an Applied Scientist, you will be responsible for the development, fine-tuning, and evaluation of AI models that power our chatbot and IVR solutions. Your work will ensure the chatbot and IVR is accurate, reliable, and continually improving to meet customer needs. This role involves collaborating with cross-functional teams to integrate AI solutions into our customer service platform, monitor their performance, and implement ongoing enhancements.

The ideal candidate has experience in successfully building chat bots using AI technologies, measuring their performance and delivering ongoing improvements.

About the team

In Project Kuiper, we believe that our differences makes us stronger. We are committed to Amazon’s culture of inclusion ingrained in our Leadership Principles, which encourages team members to seek diverse perspectives, learn and be curious, and earn trust. We want to foster a culture of collaboration, delivering results and work/life balance.

BASIC QUALIFICATIONS

– 3+ years of building machine learning models for business application experience

– PhD, or Master’s degree and 6+ years of applied research experience

– Experience programming in Java, C++, Python or related language

– Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

– Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

– Experience with large scale distributed systems such as Hadoop, Spark 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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. Dependent 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. This position will remain posted until filled. Applicants should apply via our internal or external career site.