{"id":2498368,"url":"https://alion.io/job/nextsilicon-serbia-ai-workloads-engineer","title":"Serbia- AI Workloads Engineer","company":{"id":49173,"name":"NextSilicon","domain":"nextsilicon.com","url":"https://alion.io/company/nextsilicon","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Comeet","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Belgrade, Serbia"],"countries":["RS"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"HPC","optional":false},{"name":"KV Cache","optional":false},{"name":"NCCL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-08-05T11:51:01Z","employer_posted_date":"2026-08-05","last_verified_at":"2026-10-29T15:02:01Z","board_verified":true,"closed_at":null,"days_open":85,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":85},"description":"Description\nNextSilicon 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.\nAt NextSilicon, everything we do is guided by three core values:\nProfessionalism: We strive for exceptional results through professionalism and unwavering dedication to quality and performance. \nUnity: Collaboration is key to success. That's why we foster a work environment where every employee can feel valued and heard. \nImpact: We're passionate about developing technologies that make a meaningful impact on industries, communities, and individuals worldwide.\nThe 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.\nRequirements\n4+ years of experience in software engineering.\nStrong Python and PyTorch development experience.\nSolid understanding of LLMs and modern inference workflows (e.g., KV cache, paged attention, speculative/assisted decoding, batching/scheduling)\nExperience running, profiling, and instrumenting open-source AI inference systems (e.g., vLLM or similar)\nProficiency in C++ for developing software that models or interacts with hardware execution behavior (latency, dataflow, memory access patterns).\nExperience with distributed inference and collectives (e.g., NCCL) and parallelism strategies (TP/PP/EP) is an advantage\nExperience with dynamic batching systems (e.g., vLLM, TensorRT-LLM) is an advantage\nFamiliarity with MLPerf Inference benchmarks and methodology (Server/Offline, latency constraints, request arrival patterns) is an advantage\nExperience programming custom kernels (e.g., CUDA, Triton, or similar) is an advantage\nBackground in performance analysis, simulation, compiler/runtime profiling, or workload modeling is an advantage\nResponsibilities\nModel 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.\nRun and adapt open-source AI workloads, collecting and analyzing metrics such as latency, throughput, and traversal or arrival statistics.\nUse SDK and framework-integration tools to profile full-stack behavior, identify performance bottlenecks, and drive improvements with compiler, runtime, and hardware design teams.\nPrototype custom kernels or runtime components when needed to enable or optimize new AI workflows on NextSilicon 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