We are looking for an experienced team lead for our AI pipelines team.

Company Overview

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 enterprise (in-perm) environments.

Role description:

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!

Role responsibility:

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.

Must-have requirements:

• BSc/MSc in Computer Science or Computer Engineering from the accredited university
• Managed at least 2-3 engineers
• Experience in implementing algorithms on embedded platforms
• Experience in Python programming and DL frameworks
• Proven experience in ML engineering and specifically, implementing of AI pipelines (composed of pretrained DL models and pre/post processing), data streaming, model zoo handling, and inference serving in production environments.

Advantages:

• 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.