{"id":1275972,"url":"https://alion.io/job/great-sky-ai-frameworks-engineer","title":"AI Frameworks Engineer","company":{"id":2372716,"name":"Great Sky","domain":"greatsky.ai","url":"https://alion.io/company/greatsky","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boulder, United States","Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"JAX","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Triton","optional":false}],"status":"live","first_seen_at":"2026-09-22T21:42:21Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-09-29T01:33:21Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"About Us\nGreat Sky is a technology startup based with a mission to rebuild AI from first principles. We are pursuing neuroscience-inspired hardware and algorithms that overcome the greatest challenges in scaling AI systems.\nThe Role\nWe are looking for an AI Frameworks Engineer to help build the core software layer that connects our research ideas to working, testable, scalable AI systems. This is a software engineering role focused on the internal AI framework: the abstractions, APIs, graph execution paths, training strategies, validation systems, and test infrastructure that make our research stack usable and reliable.\nKey Responsibilities\nDesign, implement, and maintain core AI framework abstractions for defining, training, validating, and executing novel graph-structured models.\n\nBuild clean Python APIs for training workflows, including loss objects, model runtime bundles, optimizer/training strategy interfaces, and more.\n\nDevelop and maintain JAX and PyTorch infrastructure for model execution, customizable training protocols, numerical parity tests, and reusable forward-pass utilities.\n\nHelp design validation systems that catch incompatible model/loss/solver/topology combinations early, with clear diagnostics for researchers and production users.\n\nOrganize research code into stable, well-tested framework components without slowing down exploration.\n\nCreate clean seams between research-mode workflows and production harness workflows, so the same infrastructure can support ad hoc experiments, custom training loops, and ticketed/cloud training runs.\n\nWrite high-quality tests for numerical behavior, protocol conformance, registry behavior, graph execution and training loops.\n\nCollaborate closely with researchers and hardware/software engineers to translate evolving research requirements into robust software architecture.\n\nImprove developer ergonomics: documentation, examples, error messages, package organization, type boundaries, and API consistency.\n\nOver time, help shape the broader AI software architecture that connects model design, simulation, training, validation, and hardware execution.\n\nQualifications\nRequired:\nBachelor's or Master's degree in Computer Science or a related field, or equivalent professional experience.\n\nStrong Python software engineering skills, with experience building libraries, frameworks, or infrastructure used by other engineers or researchers.\n\nHands-on experience with at least one modern ML framework, especially JAX or PyTorch.\n\nProficiency with training-loop internals: forward passes, losses, gradients, optimizers, metrics, parameter/state handling, and numerical testing.\n\nExperience designing clean APIs and abstractions in complex codebases.\n\nAbility to reason about graph-structured computation, model execution, dependency boundaries, and runtime state.\n\nStrong testing instincts: unit tests, integration tests, regression tests, numerical parity tests, and clear failure modes.\n\nAbility to work in a research-heavy environment where requirements evolve and the right abstraction often emerges through iteration.\n\nExcellent written and verbal communication skills, especially when translating between research ideas and maintainable engineering designs.\n\nPreferred:\nPrior experience working in an AI technology environment.\n\nExperience with typed Python, protocol-oriented design, dataclasses, Pydantic, package refactors, or public/internal SDK design.\n\nFamiliarity with multi node and multi gpu training for JAX or PyTorch\n\nExperience with custom kernel writing in Triton/Cuda/Pallas\n\nExperience designing plugin or registry systems for losses, optimizers, training strategies, model components, or execution backends.\n\nExperience with compiler-adjacent or graph-adjacent systems: computational graphs, schedulers, IRs, topology validation, graph transformations, or hardware-aware execution.\n\nExperience working near hardware teams, accelerator teams, simulation teams, or low-level performance work.\n\nFamiliarity with containers, cloud execution, job orchestration, experiment tracking, or production training harnesses.\n\nGrowth Opportunities\nThis role has a path toward broad technical ownership within Great Sky’s AI software stack.\nAs the team grows, you may help define framework architecture, set engineering standards, mentor other engineers, and lead major infrastructure projects spanning research workflows, simulation, training, validation, and hardware integration.\nFor the right person, this is a chance to build foundational infrastructure for a new kind of AI platform, rather than incrementally improving an existing transformer/GPU stack.\nBenefits and Perks\nMeaningful equity ownership in an early-stage deep tech company\n\nEmployer-matched 401(k)\n\nHealth, dental, vision, and life insurance\n\nFlexible PTO\n\nSupport for ongoing learning, conference attendance, and skill development\n\nOur culture is onsite by default (we're founded by scientists who are used to working in the lab), with flexibility for hybrid arrangements. For the right person and role, we're open to filling roles remotely","description_format":"text","description_chars":5093,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Growth opportunities","Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Hardware","Servers & Data Center Hardware","Optical Communications"],"lifecycle":[{"event":"open","at":"2026-09-26T01:36:10Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.864,"p_room":1,"age_days":5,"expected_fill_days":113,"reasons":["conf:2","velocity","win:early"],"computed_at":"2026-09-28T05:45:00Z"},"pay":{"stated_usd_annual":220000,"is_top_pay":false},"html_url":"https://alion.io/job/great-sky-ai-frameworks-engineer","json_url":"https://alion.io/job/great-sky-ai-frameworks-engineer.json","meta":{"generated_at":"2026-09-29T04:43:33Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4503,"day_limit":5000,"remaining_today":497,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}