What are the responsibilities and job description for the Senior Staff Modelling Engineer position at Prodapt?
We are looking for a Senior Staff Modelling engineer for one of our clients in Sunnyvale, CA remote role. Please apply here or reach out to me directly.
Roles and responsibilities
- Our team is building state-of-the-art machine learning SW/HW infrastructure in Facebook. We are looking for a software engineer, working on building tools to track performance metrics and facilitate performance analysis for key benchmarks that matter to the company, build up profiling infrastructure to extract more insights, and build up performance models which we can use the predict execution latency of a given model.
- ● We work on state-of-the-art machine learning solutions at huge scale. This is a unique opportunity to participate in building ML solution which need to support billions of users – it brings potential for landing huge, direct impact; on the other hand, it is a very challenging problem which calls for a sophisticated and well-executed engineering solution at top of the industry.
- ● Our teams drive end-to-end performance, which provides technical exposure to almost all areas in ML infrastructure, including ML infra, ML model building, PyTorch, runtime, compiler, firmware, hardware design, and so on. We have the freedom to either go very wide and touch many pieces or go very deep and drill on one key area of interest.
- ● Working with domain experts and seasoned engineers. Our team consists of people from deep ML and computer architecture background, and we interface with many experts in all domains mentioned above.
Requirements
- 1 Fluency in software engineering skills (e.g. source control) and programming with Python / C
- 2 Experience working with hardware acceleration (e.g., GPU, DSP, ML accelerator, CPU kernel library)
- 3 Experience in performance modeling
- 4. Relevant experience: 5 yrs (not strict, grad school experience can count)
- 5 Bachelor’s degree in computer science, similar technical field, or equivalent practical experience
- ● Good to have skills:
- 1 Experience with machine learning or HPC workloads
- 2 Experience in cross-group and cross-functional collaboration with excellent communication skills
- 3 Experience in recommendation machine learning models