Sr. Machine Learning Solutions Architect

Sr. Machine Learning Solutions Architect

About this role:

As a part of the Field Technical Sales organization, you will be working directly with our customers and Groq’s business and technical leadership to architect and promote winning solutions and business strategies. The ideal candidate has experience building, deploying, or supporting machine learning solutions in production platforms. A background in software development and AI. Large language models (LLMs), computer vision, text-to-speech, and related domains are all highly desirable. Low-level algorithm programming languages, particularly embedded domain specific languages (EDSL) such as CUDA, OneAPI, OpenCL, or HDL are a plus. Practical experience understanding algorithmic kernels and models running on accelerated hardware such as GPUs, FPGAs, DSPs, or custom ASICs is a plus. Practical experience understanding algorithmic kernels and models running on accelerated hardware such as GPUs, FPGAs, DSPs, or custom ASICs is relevant and valuable.

Responsibilities & opportunities in this role:

• Develop a deep understanding of Groq’s Language Processor Unit (LPU) and our software stack.
• Lead all technical sales activities related to customer engagements from the early stage through the successful design win stages.
• Lead early-stage technical discussions in tandem with sales account managers to present Groq product offerings.
• Uncover and understand customer solutions and identify critical technical and/or business considerations.
• Develop and articulate Groq’s unique product value messaging while positioning to target specific customer opportunities.
• Prepare and present demonstrations (demos) and proof points to gain technical credibility and advance the sales engagement.
• Work in partnership with sales account leaders in developing winning technical proposals with Groq products.
• Work closely with Groq's sales, product, and development teams to engage and support customers and partners throughout the globe to ensure the technical experience with our product is outstanding.
• Recommend product enhancements and improvements to Product Marketing teams based on first-hand knowledge and usage. 

Ideal candidates have/are:

• Technically curious problem solver with the ability to quickly understand complex technical and business challenges and synthesize and articulate back-identified opportunities.
• Experience with:
  • Computational sciences, physics, or mathematical-centric applications
  • Algorithm programming using languages such as Python, Java, Julia, Haskell, R, C++, Scala, or Matlab programming, and at least one modern machine learning framework.
  • Supporting or using PCIe accelerators such as GPUs, FPGAs, or DSPs from evaluation to production.
  • A strong technical understanding of AI/ML, the targeted applications, and competition.
  • Prior experience working in or with customers in the hyperscale data center, automotive, or high-performance compute (HPC) domains.
  • Strong writer and public speaker; operate with integrity and drive transparency, openness, and effective communication.
  • Comfortable engaging directly with customers, particularly with executive or architect-level engineering leadership

Qualifications for this role:

• MS in CS, CE/EE, Math, or Physics or related discipline with 5+ years in machine learning or similar algorithmic/computational experience in model development or deployment highly desirable. Or, a Ph.D. in computer science, math, or engineering WITH AT LEAST 4 YEARS OF INDUSTRY EXPERIENCE CODING MACHINE LEARNING or computational algorithms will also be considered.
• A proven track record of supporting customers through highly complex design cycles.
• Customer-first mindset. Driven to meet or exceed customer expectations, resolve issues expeditiously, and, when possible, proactively.
• Excellent leadership, mentoring, and cross-functional collaborative and influencing skills.
• Effective communication & and presentation skills and comfortable in a customer-facing environment.
• Able to work in a very dynamic start-up environment.
• Willingness to travel worldwide to customer locations to support customer engagements.
• May require up to 25% travel during peak periods (i.e. one week per month).
• Location Preference: North America. Mt. View, California, New York or DC area preferred.
  • Open to remote locations.