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Open nowFirst seen 4 days ago

Serbia- AI Workloads Engineer

nextsilicon/18.00727 open roles

Where
Serbia
Work mode
Hybrid
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Your applicationOpen nowSerbia- AI Workloads Engineernextsilicon/18.007 · Serbia

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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. nextsilicon/18.007 postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 4 days ago

nextsilicon/18.007 median: 1 days open

The posting

NextSilicon is reimagining high-performance computing (HPC & AI). Our accelerated compute solutions leverage intelligent adaptive algorithms to vastly accelerate supercomputers, driving them forward into a new generation. We have developed a novel software-defined hardware architecture that is achieving significant advancements in both the HPC and AI domains.

At NextSilicon, everything we do is guided by three core values:

  • Professionalism: We strive for exceptional results through professionalism and unwavering dedication to quality and performance.
  • Unity: Collaboration is key to success. That's why we foster a work environment where every employee can feel valued and heard.
  • Impact: We're passionate about developing technologies that make a meaningful impact on industries, communities, and individuals worldwide.

The AI Workloads team is responsible for modeling and enabling end-to-end AI workflows on NextSilicon’s next-generation hardware platforms. As an AI Workloads Engineer in Belgrade, you’ll build workflow modeling infrastructure, run and adapt open-source AI systems, and use real workloads to drive performance improvements from chip design through production.

Requirements

  • 4+ years of experience in software engineering.
  • Strong Python and PyTorch development experience.
  • Solid understanding of LLMs and modern inference workflows (e.g., KV cache, paged attention, speculative/assisted decoding, batching/scheduling)
  • Experience running, profiling, and instrumenting open-source AI inference systems (e.g., vLLM or similar)
  • Proficiency in C++ for developing software that models or interacts with hardware execution behavior (latency, dataflow, memory access patterns).
  • Experience with distributed inference and collectives (e.g., NCCL) and parallelism strategies (TP/PP/EP) is an advantage
  • Experience with dynamic batching systems (e.g., vLLM, TensorRT-LLM) is an advantage
  • Familiarity with MLPerf Inference benchmarks and methodology (Server/Offline, latency constraints, request arrival patterns) is an advantage
  • Experience programming custom kernels (e.g., CUDA, Triton, or similar) is an advantage
  • Background in performance analysis, simulation, compiler/runtime profiling, or workload modeling is an advantage

Responsibilities

  • Model and analyze end-to-end AI workflows (e.g., assisted decoding, dynamic batching, dynamic KV cache, MLPerf-like scenarios) on NextSilicon platforms, from simulation through production.
  • Run and adapt open-source AI workloads, collecting and analyzing metrics such as latency, throughput, and traversal or arrival statistics.
  • Use SDK and framework-integration tools to profile full-stack behavior, identify performance bottlenecks, and drive improvements with compiler, runtime, and hardware design teams.
  • Prototype custom kernels or runtime components when needed to enable or optimize new AI workflows on NextSilicon hardware.
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