We are looking for an experienced team lead for our AI pipelines team.
Company Overview:
We are 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 our 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 our 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 our 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.
Company Overview:
We are 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 our 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 our 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 our 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.
Requirements:
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 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 the 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.
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 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 the 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.
This position is open to all candidates.
