Groq is delivering industry leading performance and sub-millisecond latency with efficient, software-driven solutions for compute-intensive applications. At Groq, you will have the opportunity to work closely with some of the most talented engineers and leaders in the world to redefine compute and shape the future of machine learning.
We are looking for an exceptional machine learning software engineer or computer scientist with experience building, deploying, and supporting machine learning kernels and models as part of our Design Acceleration Team (DAT). This team will be the front line in performing the initial analysis of customer models on the Groq Platform in addition to model optimizations for key customers. As a result, you’ll work closely with our compiler team to estimate and optimize performance, and our business and sales teams to assist Groq in focusing its efforts. As such, those who have full stack experience who can both digest customer models as well as work with the encapsulating application will excel at this role.
In order to provide the best customer experience in your role, you will be tasked with the following responsibilities:
DUTIES & RESPONSIBILITIES:
- Develop a deep understanding of Groq’s ML accelerator silicon solutions, boards and systems, the Groq SDK compiler, developer tools and system software.
- Lead technical engagements with customers by taking their models and associated runtimes and get it running within the Groq environment. Subsequently you will need to estimate performance and identify opportunities for improvement.
- Collaborate with internal Compiler teams or Kernel engineers to improve performance of key customer designs.
- Over the course of the next 6-9 months, build up expertise and capabilities with TensorFlow, ONNX, and PyTorch in conjunction with Groq’s model compiler in order to develop high performance customer solutions and related training materials.
KEY SUCCESS FACTORS & COMPETENCIES:
- Technically curious problem solver with the ability to quickly understand complex technical challenges, synthesize and articulate back. An expert in ML software fundamentals.
- Experience with:
- C++ and python programming, and at least one modern machine learning framework.
- Algorithm programming using languages such as OpenCL, CUDA, OneAPI or HDL and optimizing algorithms in tools like Numpy or Matlab.
- Full stack experience with any of a variety of frameworks (e.g. OpenVino, gRPC, Spark.ML)
- Plus: Algorithm to hardware mapping skills
- A strong technical understanding of AI/ML, the targeted applications, and competition.
- Prior experience working in or with customers in the hyperscale datacenter, automotive, or high-performance compute (HPC) domains.
- Comfortable engaging directly with customers and operating with integrity and drive transparency, openness, and effective communication.
- BS in CS, CE/EE, Math, or Physics or equivalent work experience.
- 5+ machine learning or similar algorithmic/computational experience in model development or deployment.
- Recent MS/PhD computer science, math or engineering graduates with extensive hands-on experience with coding machine learning or DSP algorithms will also be considered.
- 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 & presentation skills and comfortable in a customer-facing environment.
- Able to work in a very dynamic start-up environment
- Willingness to travel to customer locations to support bring-up, debug, and porting efforts. Some roles may require up to 25% travel during peak on-site bring-up and support periods (i.e. one week per month).