Deep Learning Architect, Generative AI Innovation CenterAWS 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.
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, 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.
Key job responsibilitiesCollaborate with our applied and data scientists to build robust and scalable Generative AI solutions for business problems.Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs.Work hands-on to build scalable cloud environments for our customers to label data, build, train, tune, and deploy their models.Interact with customers directly to understand the business problem, helping and aiding them in the 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 teams, applied/data scientist teams, and product engineering teams to drive model implementations and new algorithms.About the teamAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences inspire us to never stop embracing our uniqueness.
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship, and other career-advancing resources here to help you develop into a better-rounded professional.
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.
Minimum RequirementsBachelor's degree in computer science or equivalent with 3+ years of relevant working experience.Experience with machine learning fundamentals, working knowledge of Python, and experience with deep learning frameworks such as Pytorch, TensorFlow, JAX or MXNet.3+ years of relevant experience in developing and deploying large-scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing.Bachelor's degree in computer science or equivalent with 5+ years of relevant working experience, or Master's degree in computer science or equivalent with 3+ years of working experience.Experiences related to machine learning, deep learning, NLP, CV, GNN, or distributed training.Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB, and EC2.Working knowledge of generative AI and hands-on experience in prompt engineering, deploying, and hosting Large Foundational Models.Acknowledgement of country: In the spirit of reconciliation, Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea, and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
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, disability, age, or other legally protected attributes.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information.
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