EER Poland

Inference Stack Engineer

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SeniorZdalnie·GdańskFull-time

#411203·Dodano dwa miesiące temu·2

Źródło: EER Poland

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Tech Stack / Keywords

AIPythonArchitectureC++PyTorch TensorFlow

Firma i stanowisko

EER Poland is hiring for a role focused on developing a next-generation AI inference stack designed for high-performance execution on modern and custom compute architectures.

Wymagania

Strong software engineering background with C++ and Python
Experience with performance-critical systems or compiler-related work
Understanding of AI model execution, especially transformers and LLMs
Familiarity with compute graphs, tensor operations, or execution frameworks
Ability to analyze complex systems end-to-end from model to runtime to hardware
Experience working with large codebases and system-level debugging
Strong communication skills and ability to work in cross-functional teams

Nice to have:

Experience with compiler frameworks such as LLVM, MLIR, Triton, TVM, XLA
Experience contributing to deep learning frameworks like PyTorch, TensorFlow, JAX
Understanding of GPU or accelerator execution models
Experience with kernel optimization or operator-level performance tuning
Knowledge of distributed inference systems (e.g., NCCL, RPC-based serving)
Familiarity with hardware-aware optimizations including memory hierarchy, vectorization, and scheduling

Obowiązki

Design and build components of an AI inference stack, from high-level model representation to low-level execution
Develop and extend a Python-based DSL for expressing AI workloads and kernels
Work on compiler infrastructure including:
- IR design and transformation pipelines
- graph lowering and optimization passes
- backend code generation for target execution environments
Optimize model execution for latency, throughput, memory efficiency, and numerical stability
Contribute to runtime systems responsible for model execution and scheduling
Profile and analyze inference workloads to identify system bottlenecks
Collaborate closely with hardware and systems engineers on execution efficiency
Influence architecture decisions for next-generation AI execution platforms

Benefity

Work on the core execution layer of modern AI systems
Direct impact on inference performance of large-scale AI workloads
Collaboration with experts in compilers, systems, and AI infrastructure
Highly technical environment with strong engineering autonomy
Opportunity to shape the architecture of a next-generation inference stack
Competitive compensation and flexible working model

EER Poland

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