Applied Scientist, Conversational AI ModEling and Learning

• A Master’s degree or a Bachelor’s degree with 2+ years of experience in developing machine learning models for business applications.
• Educational background in Computer Science, Computer Engineering, Machine Learning, or a related field, with relevant research experience.
• Proven experience in building machine learning models or working on data analysis projects.
• Proficiency in programming languages like Python, Java, or C++.
• Familiarity with machine learning libraries and tools such as scikit-learn, TensorFlow, or PyTorch.
• A solid understanding of fundamental machine learning concepts, including techniques in natural language processing (NLP).

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), Recommender Systems 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 building Generative AI solutions with LLMs, 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 Supervised Fine-Tuning (SFT), In-Context Learning (ICL), Learning from Human Feedback (LHF), etc. Your work will directly impact our customers in the form of novel products and services .

• Coursework or hands-on projects in machine learning, deep learning, or natural language processing.
• Experience with conversational AI systems or NLP applications through academic projects or internships.
• Familiarity with data processing frameworks such as Spark.
• Strong written and verbal communication skills, with an emphasis on effective teamwork and collaboration.
• Publications in peer-reviewed conferences related to NLP/ML is a plus (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI).

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 $129,400/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. 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.