{"id":676123,"url":"https://alion.io/job/scale-ai-staff-machine-learning-engineer-public-sector","title":"Staff Machine Learning Engineer, Public Sector","company":{"id":27,"name":"Scale AI","domain":"scale.com","url":"https://alion.io/company/scale-ai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":81,"open_postings":171,"ghost_share":0.234,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":89,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Denver, United States","Washington, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":274400,"max":343000,"currency":"USD","period":"year","gross":null,"usd_annual":343000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Fine-tuning","optional":true},{"name":"LLM","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"RLHF","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-01-30T22:10:50Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-17T09:07:49Z","board_verified":true,"closed_at":null,"days_open":259,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":259},"description":"The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale.\nOur Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge, we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators.\nYou will:\nLead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability.\nBuild and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data.\nDesign and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently.\nFine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets.\nDesign memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions.\nOwn and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts.\nDefine evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments.\nPartner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams.\nServe as a technical mentor and multiplier-raising the bar for system design, ML rigor, and production readiness across the organization.\nComfortable with light travel (approximately 10%) for customer interaction and team needs.\nThis role will require an active TS security clearance. \nIdeally You’d Have: \n8+ years of experience building and deploying applied ML systems in production environments.\nDeep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps.\nStrong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation.\nHands-on experience with retrieval systems, embeddings, or representation learning.\nProficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end.\nDemonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production.\nExperience making thoughtful tradeoffs across performance, cost, reliability, and development velocity.\nNice to Haves: \nExperience deploying ML systems into air-gapped, classified, or otherwise disconnected environments - customer data centers, on-prem infrastructure, or networks with no path to a cloud provider.\nPrior work with DoD, the intelligence community, or federal mission users - including the judgment to learn a mission well enough to know what \"correct\" means for the operator using your system.\nHands-on experience with geospatial data or GEOINT: reasoning over maps, imagery, or spatial reference systems.\nDepth in model adaptation - training or fine-tuning embedding models, instruction tuning, LoRA/PEFT, or RLHF.\nExperience building evaluation infrastructure for non-deterministic systems: LLM-as-judge, regression suites for agent behavior, or drift detection in production.\nA track record of turning a forward-deployed prototype into a supported, documented capability other engineers can deploy without you.\nCompensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.\nThe base salary range for this full-time position in the location of Washington DC is:\n$274,400—$343,000 USD\nPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.\nAbout Us:\nAt Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.\nWe believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. \nWe are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's Know Your Rights poster for additional information.\nWe comply with the United States Department of Labor's Pay Transparency provision. \nPLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.","description_format":"text","description_chars":7439,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":true,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Government","LLM & Generative AI","AI Training Data & Annotation","AI Evaluation & Observability"],"lifecycle":[{"event":"open","at":"2026-09-10T22:56:02Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.3,"p_room":0.28,"age_days":259,"expected_fill_days":89,"reasons":["conf:4","velocity","ghost","win:tail","crowd:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":343000,"is_top_pay":true},"html_url":"https://alion.io/job/scale-ai-staff-machine-learning-engineer-public-sector","json_url":"https://alion.io/job/scale-ai-staff-machine-learning-engineer-public-sector.json","meta":{"generated_at":"2026-10-17T09:18:20Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":12245,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":27},"rest":"https://alion.io/mcp/rest/get_company?id=27"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fscale-ai-staff-machine-learning-engineer-public-sector"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fscale-ai-staff-machine-learning-engineer-public-sector"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fscale-ai-staff-machine-learning-engineer-public-sector"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/scale-ai-staff-machine-learning-engineer-public-sector\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fscale-ai-staff-machine-learning-engineer-public-sector"}]}