{"id":660792,"url":"https://alion.io/job/eerpoland-workloads-engineer","title":"Workloads Engineer","company":{"id":672956,"name":"EER Poland","domain":"eerpoland.com","url":"https://alion.io/company/eerpoland","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":{"grade":"C","score":57,"open_postings":50,"ghost_share":0.72,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gdańsk, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":79000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":35},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Python","optional":false},{"name":"CUDA","optional":true},{"name":"JAX","optional":true},{"name":"OpenCL","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-05-22T13:03:04Z","employer_posted_date":"2026-05-22","last_verified_at":"2026-11-07T13:48:15Z","board_verified":true,"closed_at":null,"days_open":169,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":168},"description":"Workloads Engineer\n(AI Systems / HW-SW Optimization)\nRole Overview\nThis is not a traditional software engineering role.\nWe are looking for a Workloads Engineer responsible for translating AI models into efficient, production-ready execution on a new hardware + software stack. The role sits at the intersection of AI model understanding, systems engineering, and low-level performance optimization.\nYou will work across the full stack - from AI model structure down to hardware execution, ensuring that workloads are efficient, scalable, accurate, and robust on next-generation compute platforms.\nKey Responsibilities\nAnalyze AI model architectures (including LLMs) and translate them into optimized execution workloads for custom HW/SW platforms\n\nDesign and implement high-performance software components for AI frameworks and runtime environments\n\nOptimize AI workloads for:\nperformance (latency / throughput)\n\nmemory efficiency\n\nparallel execution\n\nnumerical accuracy and stability\n\nIdentify and remove performance bottlenecks across the stack (model → runtime → hardware)\n\nContribute to design decisions for AI execution stack and system architecture\n\nSupport deployment and scaling of AI workloads in real-world environments\n\nRequired Qualifications\nBachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field\n\n5+ years of hands-on software engineering experience (or AI model development experience)\n\nStrong programming skills in Python and C++\n\nStrong algorithmic thinking and ability to solve complex computational problems\n\nSolid understanding of AI model architectures, especially transformers and LLMs\n\nExperience in performance optimization (compute, memory, and parallelization techniques)\n\nStrong communication skills and ability to work in cross-functional teams\n\nNice to Have\nExperience with AI frameworks such as PyTorch, JAX, TensorFlow (training or inference)\n\nGPU programming experience (CUDA, OpenCL) or parallel computing systems\n\nExperience with AI performance tuning (latency, throughput, memory footprint optimization)\n\nFamiliarity with distributed systems and model deployment pipelines\n\nUnderstanding of computer architecture (CPUs, GPUs, accelerators, memory hierarchies)\n\nExperience working close to hardware / compilers / runtime systems\n\nWhat We Offer\nHighly competitive salary, employment contract (Umowa o Pracę), and a comprehensive benefits package, including Medicover healthcare coverage.\n\nWork on the performance-critical compute layer for next-generation AI accelerators\n\nDirect impact on deep learning model efficiency and latency\n\nCollaboration with experts in hardware, compilers, and systems\n\nChallenging low-level performance engineering problems at the hardware-software 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