Deep Learning Architect, ProServe GenAI Full-time

Amazon launched the Generative AI (GenAI) Innovation Center (GenAIIC) in Jun 2023 to help AWS customers accelerate enterprise innovation and success with Generative AI (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center). Customers such as Highspot, Lonely Planet, Ryanair, and Twilio are engaging with the GAI Innovation Center to explore developing generative solutions.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Key job responsibilities

Use ML and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models

Collaborate with our data scientists to create and fine tune scalable ML and Generative AI solutions for business problems

Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem

Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes

Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms

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

Arlington, VA, USA | Atlanta, GA, USA | Austin, TX, USA | Boston, MA, USA | Houston, TX, USA | Jersey City, NJ, USA | Miami, FL, USA | New York, NY, USA | San Francisco, CA, USA | Santa Clara, CA, USA

BASIC QUALIFICATIONS

– Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)

– Experience coding in Python, R, Matlab, Java or other modern programming language

– 1+ years of cloud based solution (AWS or equivalent), system, network and operating system experience

– 2+ years of experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inferences)

– 2+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience

PREFERRED QUALIFICATIONS

– Masters or PhD degree in computer science, or related technical, math, or scientific field

– Strong working knowledge of deep learning, machine learning and statistics

– Experiences related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2

– Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training

– Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts

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.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/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.