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Description

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints.

We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in developing LLM solution, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions.

Key job responsibilities

As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases. Your work will directly impact our customers in the form of novel products and services .

We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA | Boston, MA, USA | Seattle, WA, USA | Sunnyvale, CA, USA

Basic Qualifications

• PhD, or Master's degree and 2+ years of building machine learning models or developing algorithms for business application experience

• 3+ years of programming in Java, C++, Python or related language experience

• 3+ years’ experience with modeling languages and tools like PyTorch / TensorFlow, R, scikit-learn, numpy, scipy, etc.

• Graduate degree (MS or PhD) in Computer Science, Electrical Engineering, Mathematics or a related field.

• Solid ML background and familiar with standard NLU, NLG, and LLM techniques

Preferred Qualifications

• PhD in Computer Sciences, Electrical Engineering, or Mathematics with specialization in machine learning, deep learning, or natural language processing

• 1+ years experience in building conversational AI and/or natural language processing systems.

• Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, etc.)

• Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

• 2+ years 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 $136,000/year in our lowest geographic market up to $222,200/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.