{"id":307696,"url":"https://alion.io/job/scaffold-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":456106,"name":"Scaffold","domain":"getscaffold.com","url":"https://alion.io/company/scaffold-3","size_band":null,"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":"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":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":138000,"max_usd":262000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":817},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-04T21:25:07Z","employer_posted_date":"2026-09-04","last_verified_at":"2026-09-29T17:26:12Z","board_verified":true,"closed_at":null,"days_open":25,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":25},"description":"We are hiring a Machine Learning Engineer to design, build, and deploy AI systems that sit at the core of Scaffold’s platform.\nThis is not a “model-only” role. You will operate as a product-minded engineer, working across data pipelines, model development, and production systems to deliver real-world impact.\nYou will help define how AI is applied across:\nWorkflow automation (POs, schedules, change orders)\n\nData normalization and enrichment\n\nPredictive insights (delays, risk, capacity)\n\nAgent-based systems interacting with builder/trade ecosystems\n\nAbout Scaffold\nScaffold is building the data orchestration layer for residential construction. We integrate fragmented systems across builders, subcontractors, and suppliers to automate workflows, eliminate manual work, and unlock real-time decision-making.\nWe are now embedding AI deeply into this system - transforming raw, messy construction data into intelligent automation, predictive insights, and agent-driven workflows.\nWhat You’ll Do:\nBuild AI-Powered Product Features\nDesign and deploy machine learning models that operate on real-world construction data\n\nDevelop LLM-powered workflows for document parsing, communication, and automation\n\nBuild intelligent agents that interact with external systems (builder portals, ERPs\n\nOwn the End-to-End ML Lifecycle\nIngest, clean, and structure messy third-party data\n\nTrain, evaluate, and iterate on models in production\n\nDesign feedback loops to continuously improve performance\n\nWork Across the Stack\nIntegrate ML systems into backend services and APIs\n\nCollaborate on data pipelines and infrastructure\n\nPartner with frontend engineers to expose AI capabilities in product\n\nDrive Architecture & Strategy\nEvaluate model approaches (LLMs, fine-tuning, retrieval, traditional ML)\n\nDefine scalable patterns for deploying AI across customers\n\nContribute to long-term AI roadmap and product direction\n\nCollaborate Cross-Functionally\nWork closely with product, engineering, and customers\n\nTranslate ambiguous problems into production-ready solutions\n\nProvide technical leadership on AI initiatives\n\nWhat We’re Looking For:\nCore Requirements\n3-6+ years of experience in ML engineering, applied AI, or related roles\n\nStrong programming skills (Python required; familiarity with Node/TypeScript a plus)\n\nExperience building and deploying ML models in production environments\n\nFamiliarity with LLMs, prompt engineering, and modern AI tooling\n\nStrong understanding of data pipelines, APIs, and distributed systems\n\nPreferred Experience\nExperience with:\nLLM frameworks (LangChain, LlamaIndex, etc.)\n\nVector databases / retrieval systems\n\nData processing at scale (Spark, Airflow, etc.)\n\nExposure to real-world noisy data environments (not just clean datasets)\n\nExperience building internal tools or automation systems\n\nMindset\nProduct-oriented: you care about outcomes, not just models\n\nSystems thinker: you design for scale and reliability\n\nBuilder: you take ownership and move fast in ambiguous environments\n\nCurious: you stay on the frontier of AI capabilities\n\nWhy Join Scaffold?\nImpact: Play a critical role in defining and building the future of Scaffold and the residential construction industry.\n\nGrowth Opportunity: Be an early leader in a venture-backed company.\n\nCulture: Work alongside high-caliber teammates in a no-ego, high-energy environment.\n\nCompensation: Competitive salary and meaningful equity in the company.","description_format":"text","description_chars":3424,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-05T15:34:56Z"}],"liveness":{"score":36,"band":"fade","label":"Fading","p_open":1,"p_active":0.656,"p_room":0.55,"age_days":24,"expected_fill_days":23,"reasons":["conf:1","velocity","win:tail"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/scaffold-senior-machine-learning-engineer","json_url":"https://alion.io/job/scaffold-senior-machine-learning-engineer.json","meta":{"generated_at":"2026-09-30T03:02:13Z","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":2337,"day_limit":5000,"remaining_today":2663,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}