ML Engineering Team Lead
We are looking for an experienced team lead for our AI pipelines team.
Neureality is developing an innovative HW/SW computing platform for DL inference acceleration which sets new, unprecedented, bars of high-performance and cost. Our platforms are targeted for cloud and enterprises (in-perm) environments.
You will lead a small talented core team of Neureality R&D which is responsible for the following main deliverables:
- Designing, analyzing, and optimizing workloads from various sources (open source, customer provided, home-grown) on Neureality platforms. The focus is on workloads for NLP, speech, and computer-vision.
- Benchmarking and competitive analysis of workloads on other inference acceleration platforms.
- Working directly with customers on new requirements and efficient deployment of their workloads on Neureality platform
- Identifying missing gaps and new requirements for SW/HW to improve workload performance and efficient deployment.
This is an exciting opportunity to work on cutting-edge and emerging technologies, across multi-disciplinary domains of deep-learning models and computer architectures.
This is not a position of data science!
You will lead a small engineering team (3-5 engineers)
- Provide both technical and managerial leadership.
- Participate in design reviews, perform code reviews, and take part in coding tasks.
- Foster a collaborative and innovative team culture, ensuring effective communication and knowledge sharing.
- BSc/MSc in Computer Science or Computer Engineering from the accredited university
- Strong hands-on in Python programming and DL frameworks (mainly PyTorch)
- Proven experience in ML engineering and specifically, developing of AI pipelines (composed of pretrained DL models and pre/post processing), data streaming, model zoo handling, and inference serving in production environments.
- Experience as a technical lead of small R&D SW teams.
- Experience using Nvidia tools and leveraging CPU+GPU instances on cloud or on-premises for development and for in-production deployment.
- Experience with C++ and software programming principles (e.g., OOP, design patterns)
- Working with remote (offshore) partners.