Jump to content

COMPLETE Principal GenAI Specialist Solutions Architect, Training & Inference - Austin

23 days ago


 Share

Job Opportunity Details

Type

Full Time

Salary

Not Telling

Work from home

No

Weekly Working Hours

Not Telling

Positions

Not Telling

Working Location

Austin, Austin, TX, United States   [ View map ]

Job Description

Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)? You will be part of the core worldwide GenAI Training and Inference team, responsible for defining, building, and deploying targeted strategies to accelerate customer adoption of our services and solutions across industry verticals. You will be working directly with the most important customers (across segments) in the GenAI model training and inference space helping them adopt and scale large-scale workloads (e.g., foundation models) on AWS, model performance evaluations, develop demos and proof-of-concepts, developing GTM plans, external/internal evangelism, and developing demos and proof-of-concepts.

Key job responsibilities
You will help develop the industry’s best cloud-based solutions to grow the GenAI business. Working closely with our engineering teams, you will help enable new capabilities for our customers to develop and deploy GenAI workloads on AWS. You will facilitate the enablement of AWS technical community, solution architects and, sales with specific customer centric value proposition and demos about end-to-end GenAI on AWS cloud.

You will possess a technical and business background that enables you to drive an engagement and interact at the highest levels with startups, Enterprises, and AWS partners. You will have the technical depth and business experience to easily articulate the potential and challenges of GenAI models and applications to engineering teams and C-Level executives. This requires deep familiarity across the stack – compute infrastructure (Amazon EC2, Lustre), ML frameworks PyTorch, JAX, orchestration layers Kubernetes and Slurm, parallel computing (NCCL, MPI), MLOPs, as well as target use cases in the cloud.

You will drive the development of the GTM plan for building and scaling GenAI on AWS, interact with customers directly to understand their business problems, and help them with defining and implementing scalable GenAI solutions to solve them (often via proof-of-concepts). You will also work closely with account teams, research scientists, and product teams to drive model implementations and new solutions.

You should be passionate about helping companies/partners understand best practices for operating on AWS. An ideal candidate will be adept at interacting, communicating and partnering with other teams within AWS such as product teams, solutions architecture, sales, marketing, business development, and professional services, as well as representing your team to executive management. You will have a natural appetite to learn, optimize and build new technologies and techniques. You will also look for patterns and trends that can be broadly applied across an industry segment or a set of customers that can help accelerate innovation.

This is an opportunity to be at the forefront of technological transformations, as a key technical leader. Additionally, you will work with the AWS ML and EC2 product teams to shape product vision and prioritize features for AI/ML Frameworks and applications. A keen sense of ownership, drive, and being scrappy is a must.

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

Austin, TX, USA

Basic Qualifications:

- Bachelor’s degree in technical discipline with 5+ years of non-internship experience in software engineering, technical design, implementation, consulting experience.
- Experience with one or more general purpose and scripting programming languages, including but not limited to: Python, Go, C/C++, JavaScript.
- Experience managing ML models across training, inference, MLOPs, and/or developing AI applications.
- Deep hands-on understanding of deep learning and other ML algorithms and infrastructure.
- Strong verbal and written communications skills and ability to lead effectively across organizations.
- Solid communication skills, business, and financial acumen.

Preferred Qualifications:

- Master’s Degree or PhD in Engineering or related STEM field.
- 10+ years of non-internship experience in technical roles in Computational Science, High Performance Computing (HPC), DevOps, performance modeling & benchmarking, Machine Learning engineering
- 2+ years of experience training large models across compute types (e.g., GPUs, custom instances), and developing applications powered by GenAI models.
- 2+ years of leadership experience in a technical, customer-facing role in the technology industry.
- Thorough understanding of the AI/ML technology stack including but not limited to: PyTorch, JAX, MegatronLM, NemoMegatron, NCCL, CUDA
- Experience with cloud computing, HPC technologies (Lustre, MPI, Infiniband, Slurm), containers (Kubernetes, Docker, Singularity, Enroot/Pyxis)
- Experience in benchmarking and performance profiling for computational applications or machine learning stacks
- Experience with AWS services (Amazon EC2, Amazon S3, Amazon FSx for Lustre, Amazon EFA, Amazon EBS).


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.


More Information

Application Details

  • Organization Details
    Amazon Web Services, Inc.
 Share


User Feedback

Recommended Comments

There are no comments to display.

Join the conversation

You are posting as a guest. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.

Guest
Add a comment...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.

Loading...
×
×
  • Create New...