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Software Engineer - ML Systems & AI Infrastructure

orient path_ • Austria
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Build and optimize production infrastructure for LLM model compression and inference. Develop high-performance ML systems focusing on quantization, pruning, and GPU execution. Requires strong software engineering fundamentals and deep expertise in GPU performance and PyTorch.

Key Highlights
Developing the engineering layer to turn LLM compression research into reliable ML infrastructure
Focus on the intersection of models and hardware, including quantization and GPU kernels
High ownership role working directly with founders and researchers in a small technical team
Key Responsibilities
Build production infrastructure around LLM compression and inference
Develop quantization, pruning, and retraining pipelines
Optimize GPU execution, performance profiling, and benchmarking
Turn research and experimental code into reusable, reliable engineering systems
Investigate and resolve performance bottlenecks through profiling and implementation
Technical Skills Required
Python PyTorch GPU Performance
Benefits & Perks
€70K–120K base salary
Equity participation
Visa sponsorship
Relocation support
Nice to Have
CUDA/Triton or GPU kernels
vLLM/TensorRT-LLM/llama.cpp
FSDP/ZeRO/DDP
NCCL and multi-GPU systems
Profiling with Nsight or similar tools
Open-source ML infrastructure contributions

Job Description

At Orient Path, we partner with high-growth technology companies globally.

One of our clients is an early-stage deep-tech AI company developing a fundamentally new approach to LLM model compression — making foundation models smaller, faster, and more efficient to run in production.

Their research team develops compression methods. Now they are building the engineering layer that turns this research into reliable, high-performance ML infrastructure.

What are we building?

Production infrastructure around LLM compression and inference.

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