ML Application Engineer
Kraków, Małopolskie, PL
NeuReality
NeuReality is the first complete, system-level solution designed to address the challenges of optimizing, deploying, managing, and scaling AI workflows.Description
We are looking for an experienced AI/ML engineer to join our growing 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 (on-perm) environments.
Role description:
- You will join the core AI/ML Pipeline development 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, computer vision and LLMs.
- 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!
Requirements
- BSc/MSc in Computer Science or Computer Engineering from an accredited university
- 2-3 years of hands-on experience in Python programming and DL frameworks (mainly PyTorch)
- Experience developing AI pipelines inference composed of trained DL models and pre/post-processing.
- Experience in implementing algorithms utilizing Cuda or OpenCL or C or C++
- Experience in hardware/embedded system is an advantage
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Computer Science Computer Vision CUDA Engineering LLMs Machine Learning NLP Open Source Pipelines Python PyTorch R R&D
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