Sr. Deep Learning Architect, ProServe GenAI

Houston, TX, United States

Description

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.

Were 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.

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, provide data labeling support and evaluate workflows for Generative AI solutions

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

Ensure the system is scalable and capable of handling large datasets and high-demand workloads to support Gen AI initiatives.

A day in the life

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazons culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

About the team

Why AWS?

Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Mentorship & Career Growth

Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, theres nothing we cant achieve in the cloud.

Sales, Marketing and Global Services (SMGS)

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.

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

Arlington, VA, USA | Atlanta, GA, USA | Boston, MA, USA | Chicago, IL, USA | Herndon, VA, USA | Houston, TX, USA | New York, NY, USA | Washington, DC, USA

Basic Qualifications

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

- At least 5 years of experience in designing, building, and/or operating large scale enterprise IT systems in a production environment

- At least 3 years of public cloud computing experience in AWS or other large scale cloud providers

- Relevant experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)

- Experience coding in Python, R, Matlab, Java or other modern programming languages

Preferred Qualifications

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

- Strong working knowledge of deep learning, machine learning, generative AI, and statistics

- Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Caffe, Torch, Theano or similar and deep learning (e.g., CNN, RNN, LSTM)

- Strong communication skills, with attention to detail and ability to convey 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/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.

#J-18808-Ljbffr