Easter Seals Jobs

Description

The Shopping Conversation Foundation (SCF) team at Amazon is dedicated to providing foundational capabilities that enable Product, Engineering and Science teams across Rufus, Search, and Alexa Shopping to build, evaluate, and improve large language model (LLM)-based shopping experiences. Our focus areas involve evaluating the quality of the customer experience of AI powered applications, enhancing the customer experience by providing LLMs with up-to-date world knowledge from first-party and third-party data sources, serving high-quality training data for new LLM features (e.g., Multimodal) and Alexa Shopping Remarkable Alexa (RA), and building, serving, and maintaining trustworthy datasets for Rufus and Alexa Shopping.

As a Senior Machine Learning Engineer in the SCF org, you will specialize in building engineering solutions for information retrieval problems on unstructured and noisy data at internet scale. You’ll tackle challenges such as retrieving relevant information from vast amounts of unstructured data sources like product specifications, expert opinions and customer reviews. You will need to develop innovative techniques to handle noise and ambiguity in natural language data while ensuring high precision and recall. Success in this role requires a deep understanding of machine learning, information retrieval techniques, natural language processing, and the ability to stay up-to-date with the latest advancements. Additionally, you will need to make high-judgment decisions when proposing trade-offs between factors such as model accuracy, computational efficiency, and data privacy, and work closely with cross-functional stakeholders to understand business requirements and propose innovative solutions.

We embrace a collaborative and inclusive culture where diverse perspectives are valued, and creativity thrives. We foster a growth mindset, continuously learning and pushing the boundaries of what's possible in the field of machine learning, generative AI and natural language processing.

Key job responsibilities

• Research, design, and develop cutting-edge information retrieval and natural language processing solutions to address complex challenges in the shopping domain, such as retrieving relevant information from unstructured and noisy data sources at internet scale.

• Design, develop, test, and deploy inference solutions for high-end large language models (LLMs) and other machine learning models, ensuring efficient and reliable performance in production environments.

• Investigate and implement inference optimization techniques, such as model quantization, pruning, and hardware acceleration, to improve the performance and cost-effectiveness of deployed models.

• Operationalize machine learning models by following best practices for model deployment, monitoring, and maintenance, ensuring seamless integration with existing systems and infrastructure.

• Mentor and guide junior machine learning engineers, fostering their growth and development through knowledge sharing, code reviews, and hands-on coaching.

• Contribute to the overall growth and development of the team by staying up-to-date with the latest advancements in machine learning, information retrieval, and natural language processing, and sharing your expertise through technical presentations, documentation, and training sessions.

Basic Qualifications

• 5+ years of non-internship professional software development experience

• 3+ years of experience building solutions using machine learning

• 5+ years of programming with at least one software programming language experience

• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

• Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

• Good Experience of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

• Bachelor's degree in computer science or equivalent

• Experience with Python, PyTorch, and Java programming and performance optimization

• Good understanding of Machine Learning algorithms and techniques

• Experience with Large Language Model inference, especially TensorRT-LLM and Trainium development

• Excellent problem-solving skills, with the ability to think creatively and critically about complex problems

• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams

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 $151,300/year in our lowest geographic market up to $261,500/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.