Workloads Engineer
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SeniorFull-time·Umowa o pracę
#411205·Dodano wczoraj·0
Źródło: EER PolandTech Stack / Keywords
AIPythonPyTorchTensorFlowCUDAOpenCLArchitecture
Firma i stanowisko
EER Poland is the hiring organization for this role located in Gdansk, Poland.
Wymagania
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field
- 5+ years of hands-on software engineering or AI model development experience
- Strong programming skills in Python and C++
- Strong algorithmic thinking and problem-solving ability
- Solid understanding of AI model architectures, especially transformers and LLMs
- Experience in performance optimization including compute, memory, and parallelization techniques
- Strong communication skills and ability to work in cross-functional teams
Nice to have:
- Experience with AI frameworks such as PyTorch, JAX, TensorFlow (training or inference)
- GPU programming experience (CUDA, OpenCL) or parallel computing systems
- Experience with AI performance tuning for latency, throughput, and memory footprint
- Familiarity with distributed systems and model deployment pipelines
- Understanding of computer architecture including CPUs, GPUs, accelerators, and memory hierarchies
- Experience working close to hardware, compilers, and runtime systems
Obowiązki
- Analyze AI model architectures including LLMs and translate them into optimized execution workloads for custom hardware and software platforms
- Design and implement high-performance software components for AI frameworks and runtime environments
- Optimize AI workloads for latency, throughput, memory efficiency, parallel execution, numerical accuracy, and stability
- Identify and remove performance bottlenecks across the stack (model to runtime to hardware)
- Contribute to design decisions for AI execution stack and system architecture
- Support deployment and scaling of AI workloads in real-world environments
Benefity
- Highly competitive salary with an employment contract (Umowa o Pracę)
- Comprehensive benefits package including Medicover private healthcare
- Opportunity to work on performance-critical compute layers for next-generation AI accelerators
- Direct impact on deep learning model efficiency and latency
- Collaboration with experts in hardware, compilers, and systems
- Challenges involving low-level performance engineering at the hardware–software boundary
Opieka zdrowotna
EER Poland
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