Machine Learning Solutions Engineer
Cerebras is looking for an exceptional ML Solutions Engineer to work closely with our customers – leaders in industry and academia — on a diverse set of machine learning applications, both commercial and scientific. In this role, you will work with world-class domain experts to enable cutting-edge deep learning research with the Cerebras Wafer Scale Engine, the largest chip in the world dedicated for AI compute.
If you are passionate about driving the next generation of deep learning applications and want to lead these projects to impact use cases across verticals from Health Care and Life Sciences, to Financial Services, to Media and Entertainment, to Manufacturing, to Technology, and more, then we invite you to join our world-class Solutions Engineering team.
- Work with our customers to understand their business and research use cases and the types of deep learning models they are interested in unlocking with Cerebras hardware.
- Create high-level performance estimates for particular customer problems and help users understand how their workloads will be executed on the CS-1.
- Write or directly adapt prototype Tensorflow/PyTorch model code for customer use cases and be the first to bring up these new networks on the CS-1.
- Run experiments with customer models on our system.
- As the voice of the customer and part of the broader product team, you will work directly with the product management team to inform product requirements and shape the future of our product. This role requires a breadth of knowledge from understanding deep learning models and being familiar with recent advances in this area, to being experienced with ML frameworks, algorithmic debug/analysis, and performance modelling. The role will have an enormous impact on the speed at which we can deliver new types of deep learning solutions on our software/hardware platform and will influence the next generations of our software/hardware platform.
- BS or MS degree in Computer Science or related field
- 2+ years of related work experience as a software engineer
- Strong debugging skills, experience with debugging complex software stack and hardware systems
- Familiarity with recent deep learning models in computer vision, natural language processing, sequence modelling
- Experience with Python/bash, TensorFlow or PyTorch
- Proactive, “do-it-yourself” attitude
- Curiosity, desire and ability to learn quickly and be involved in diverse work
- Ability to multitask effectively in a dynamic environment
- Strong analytical and problem solving skills
- Excellent verbal and written communications skills with the ability to effectively collaborate with customers, management and engineering