{"id":2916424,"url":"https://alion.io/job/femtosense-ml-compiler-engineer","title":"ML Compiler Engineer","company":{"id":3784215,"name":"FEMTOSENSE","domain":"femto.ai","url":"https://alion.io/company/femto-2","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Bruno, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":106000,"max_usd":236000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":370},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache TVM","optional":false},{"name":"C++","optional":false},{"name":"LLVM","optional":false},{"name":"MLIR","optional":false},{"name":"ONNX","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"XLA","optional":false},{"name":"Quantization","optional":true}],"status":"live","first_seen_at":"2026-04-15T00:00:00Z","employer_posted_date":"2026-04-15","last_verified_at":"2026-10-24T19:28:57Z","board_verified":true,"closed_at":null,"days_open":192,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":192},"description":"You will work on a custom ML compiler that transforms modern ML and DSP models into highly efficient programs for our accelerator.\nThis role spans the full compiler stack-from ingesting models and transforming intermediate representations to optimizing execution under tight memory and latency constraints.\nWhat You’ll Do\nBuild and maintain model ingestion pipelines (e.g., PyTorch / ONNX → internal IR)\nImplement graph transformations such as:\nOperator decomposition and canonicalization\nShape inference and layout transformations\nDevelop and extend intermediate representations (e.g., MLIR)\nImplement optimization passes including:\nOperator fusion and graph partitioning\nBasic scheduling and tiling strategies\nMemory planning and reuse\nDebug correctness and numerical issues across transformations\nCollaborate with hardware and ML teams to improve system performance\nRequirements\nRequired qualifications and experience:\n2+ years of experience in compilers and/or edge-AI\nProficiency in Python and/or C++\nExperience with at least one:\nMLIR, LLVM, TVM, XLA, or similar\nGraph-level transformations or ML model internals\nUnderstanding of deep learning models (conv, sequence models, etc.)\nAbility to reason about correctness and performance tradeoffs\nNice to have:\nExperience with optimization techniques (tiling, scheduling, memory reuse)\nFamiliarity with ONNX or PyTorch internals\nExposure to quantization or low-precision computation\nInterest in hardware-aware ML systems\nBenefits\n401(k)\nMedical insurance\nVision insurance\nDental insurance\nCommuter benefits\nDisability insurance\nPaid maternity leave\nPaid paternity leave\nChild care support\nfemtoAI is an equal opportunity employer committed to a diverse workforce which strives to create an inclusive working environment empowering everyone to do their best work. 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