{"id":118892,"url":"https://alion.io/job/shield-ai-senior-staff-engineer-ml-ops-r4941","title":"Senior Staff Engineer, ML Ops (R4941)","company":{"id":50,"name":"Shield AI","domain":"shield.ai","url":"https://alion.io/company/shield-ai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":74,"open_postings":91,"ghost_share":0,"stale_share":0.846,"repost_share":0.011,"time_to_fill_p50_days":66,"computed_at":"2026-11-05T05:54:30Z"}},"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":["San Diego, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":233000,"max":350000,"currency":"USD","period":"year","gross":null,"usd_annual":350000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Go","optional":false},{"name":"Helm","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Terraform","optional":false},{"name":"Transformers","optional":false},{"name":"Grafana","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"Ray","optional":true},{"name":"SLURM","optional":true}],"status":"live","first_seen_at":"2026-05-14T07:16:12Z","employer_posted_date":"2026-05-14","last_verified_at":"2026-11-05T23:05:36Z","board_verified":true,"closed_at":null,"days_open":175,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":175},"description":"Job Description:\nShield AI builds autonomy systems for defense applications, including air, maritime, and space platforms operating in complex and contested environments.\nWe are building the AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating, and deploying next-generation AI systems.\nThe AI Factory serves two purposes. Internally, it powers autonomy development across Hivemind and other AI programs. Externally, it becomes the reference architecture deployed into customer environments, spanning commercial cloud, on-premise infrastructure, sovereign deployments, and fully air-gapped systems.\nWe are looking for a Senior Staff Engineer to help define and build this platform. You will partner closely with ML researchers, platform engineers, and autonomy teams to deliver an exceptional developer experience for training and deploying modern AI models.\nSuccess in this role requires balancing researcher productivity, platform simplicity, operational excellence, and long-term maintainability. You will work hands-on across the stack, helping shape both the platform architecture and its implementation while staying closely aligned with the rapidly evolving AI ecosystem.\nWhat you'll do:\nAI Platform Development: Lead the design and implementation of the AI Factory Reference Architecture, delivering a Kubernetes-native platform for AI development, distributed training, simulation, evaluation, and deployment.\nAI Research Enablement: Partner directly with ML researchers to understand evolving training workflows and ensure the platform supports state-of-the-art AI frameworks, foundation model development, reinforcement learning, distributed training, and emerging research workflows.\nDeveloper Experience: Design self-service AI development workflows that enable engineers to move seamlessly from local experimentation to large-scale distributed execution using familiar open source tools and frameworks.\nDistributed AI Infrastructure: Build the infrastructure required to support distributed training, simulation, inference, and reinforcement learning workloads. Evaluate and integrate orchestration, scheduling, and resource management technologies to maximize scalability and developer productivity.\nCompute Platform: Design and optimize shared GPU infrastructure across cloud and on-premises environments. Improve resource utilization, scheduling efficiency, storage, networking, observability, and overall platform reliability.\nData & Model Lifecycle: Build platform capabilities that enable dataset management, experiment tracking, artifact management, model versioning, evaluation, deployment, monitoring, and continuous model improvement.\nPlatform Distribution: Develop repeatable deployment and lifecycle management solutions using Infrastructure as Code and modern platform engineering practices. Support commercial cloud, customer-managed infrastructure, sovereign environments, and fully air-gapped deployments.\nTechnology Leadership: Evaluate emerging AI infrastructure technologies and establish architectural patterns that balance scalability, performance, maintainability, and developer experience.\n Cross-Functional Collaboration: Work closely with AI researchers, autonomy teams, infrastructure engineers, and product teams to ensure the platform evolves alongside customer needs and advances in AI.\nKey Outcomes:\nEngineers move from idea to distributed training in hours instead of days.\nHigh GPU utilization through efficient scheduling with KAI on Kubernetes.\nResearchers use modern AI tooling without unnecessary platform friction.\nAI Workspaces become the standard development environment across autonomy programs.\nTraining, simulation, evaluation, and deployment operate as a unified platform.\nThe AI Factory Reference Architecture can be deployed consistently across cloud, on-premise, and air-gapped environments.\nPlatform capabilities are reusable across multiple autonomy programs and customer deployments.\nRequired qualifications:\nExperience building Kubernetes-native AI or MLOps platforms supporting distributed machine learning workloads.\nDeep understanding of modern AI training frameworks, including PyTorch, Hugging Face Transformers and distributed training techniques.\nExperience operating GPU-accelerated infrastructure and distributed training systems.\nStrong understanding of Kubernetes, Linux, networking, security, storage, and distributed systems.\nExperience with GPU scheduling concepts and large-scale AI workloads.\nExperience packaging and deploying cloud-native infrastructure using Terraform and Helm.\nStrong software engineering skills in Python and Golang and modern cloud-native technologies.\nExperience collaborating closely with ML researchers to translate research workflows into scalable platform capabilities.\nPreferred qualifications:\nExperience with Ray or other distributed AI orchestration frameworks.\nExperience with KAI, Slurm or other GPU scheduling technologies.\nExperience supporting reinforcement learning, simulation-driven training, robotics, or autonomy workloads.\nExperience deploying and optimizing AI models for edge hardware.\nExperience designing infrastructure for classified, sovereign, or air-gapped environments.\nExperience with observability technologies such as OpenTelemetry, Prometheus, and Grafana.\nExperience contributing to or maintaining open-source infrastructure projects.\nWhy Join Us\nThe AI Factory is the foundation for how Shield AI develops and deploys autonomy.\nAs a Senior Staff Engineer, you will help build the reference architecture used internally by our engineering teams and delivered to customers building their own AI capabilities. Your work will directly impact how quickly researchers can iterate, how efficiently compute resources are utilized, and how AI systems move from experimentation to operational deployment.\nThis is an opportunity to work at the intersection of modern AI, distributed systems, Kubernetes, and defense, building a platform that enables the next generation of autonomy systems while leveraging the best of the open-source AI ecosystem.","description_format":"text","description_chars":6123,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Military Drones","Defense Manufacturing","Defense AI","Drone AI"],"lifecycle":[{"event":"open","at":"2026-05-14T07:16:12Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 2","filings_12m":2,"filings_prev_12m":2,"green_card_filings_12m":0,"median_offered_wage_usd":132500,"route":null,"cap_exempt":false,"checked_at":"2026-10-29T16:27:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":1}],"liveness":{"score":13,"band":"cold","label":"Long shot","p_open":1,"p_active":0.473,"p_room":0.28,"age_days":174,"expected_fill_days":66,"reasons":["conf:3","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-11-05T05:54:30Z"},"pay":{"stated_usd_annual":350000,"is_top_pay":true},"html_url":"https://alion.io/job/shield-ai-senior-staff-engineer-ml-ops-r4941","json_url":"https://alion.io/job/shield-ai-senior-staff-engineer-ml-ops-r4941.json","meta":{"generated_at":"2026-11-06T02:31:11Z","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":4260,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-07T00:00:00Z"}},"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":50},"rest":"https://alion.io/mcp/rest/get_company?id=50"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fshield-ai-senior-staff-engineer-ml-ops-r4941"},{"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%2Fshield-ai-senior-staff-engineer-ml-ops-r4941"},{"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%2Fshield-ai-senior-staff-engineer-ml-ops-r4941"},{"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/shield-ai-senior-staff-engineer-ml-ops-r4941\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fshield-ai-senior-staff-engineer-ml-ops-r4941"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":118892}},{"tool":"search_jobs","arguments":{"company":"shield.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":118892},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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