{"id":1491111,"url":"https://alion.io/job/lmi-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":721749,"name":"LMI","domain":"lmisolutions.com","url":"https://alion.io/company/lmisolutions","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":{"grade":"A","score":100,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":9,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":135000,"max":230000,"currency":"USD","period":"year","gross":null,"usd_annual":230000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Fluent Bit","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"Linux","optional":false},{"name":"OpenSearch","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Service Mesh","optional":false},{"name":"TCP/IP","optional":false},{"name":"Terraform","optional":false},{"name":"Zero Trust","optional":false}],"status":"live","first_seen_at":"2026-09-30T00:44:32Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-01T07:32:47Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Overview\nLMI is seeking a Platform Engineer to design, deploy, operate, and sustain secure cloud-native platform capabilities for a Department of War mission partner. This remote role will focus on Amazon Web Services (AWS)-hosted Kubernetes environments that connect to and operate within the Department of Defense Information Network (DODIN). The Platform Engineer will support platform architecture, infrastructure automation, container orchestration, application onboarding, cybersecurity compliance, observability, troubleshooting, and continuous service improvement. The ideal candidate is a hands-on engineer who can translate mission and application requirements into reliable, repeatable, secure, and supportable platform services.\nLMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.\nLeveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors, helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.\nThis is a remote position within the continental United States and requires an active Secret security clearance. The employee must be available during core working hours aligned to the mission partner and may be required to travel periodically to government or LMI locations for integration, testing, maintenance, or mission support.\nResponsibilities\nDesign, deploy, configure, operate, and sustain AWS-based platform services supporting mission-critical Department of War applications and workloads.\nAdminister Kubernetes clusters and supporting services, including cluster configuration, node groups, namespaces, role-based access control, ingress, service discovery, storage, secrets management, network policies, autoscaling, upgrades, and lifecycle maintenance.\nBuild and maintain repeatable infrastructure and platform configurations using infrastructure-as-code tools such as Terraform, AWS CloudFormation, or equivalent customer-approved technologies.\nDevelop, maintain, and improve continuous integration and continuous delivery pipelines, GitOps workflows, container registries, artifact repositories, automated testing, and deployment controls.\nOnboard, configure, deploy, and sustain containerized applications across development, test, staging, and production environments.\nIntegrate platform services with DODIN network services, identity and access management, public key infrastructure, logging, monitoring, vulnerability management, endpoint security, and other government enterprise services.\nImplement and maintain secure platform configurations aligned with approved security baselines, Defense Information Systems Agency Security Technical Implementation Guides, Risk Management Framework requirements, and Authority to Operate conditions.\nMonitor platform availability, performance, capacity, security posture, and application health using AWS-native and customer-approved observability tools.\nTroubleshoot complex issues involving Linux, containers, Kubernetes, AWS services, networking, Domain Name System, certificates, encryption, load balancing, storage, compute, identity, and application dependencies.\nPerform platform patching, vulnerability remediation, configuration management, backup, recovery, and controlled upgrade activities while minimizing mission disruption.\nCollaborate with cybersecurity, network, software, data, systems engineering, and mission teams to resolve dependencies and deliver integrated capabilities.\nDevelop and maintain platform architecture documentation, configuration standards, operating procedures, runbooks, troubleshooting guides, deployment instructions, and knowledge articles.\nSupport technical interchange meetings, architecture reviews, release planning, change control, incident response, root-cause analysis, and after-action reviews.\nProvide clear status reporting on platform health, technical risk, security findings, maintenance activities, dependencies, and recommended actions.\nParticipate in scheduled maintenance and time-sensitive incident response outside normal working hours when required by mission needs.\nQualifications\nRequired Qualifications:\nActive Secret security clearance.\nMinimum of five years of directly relevant professional experience in platform engineering, cloud engineering, DevSecOps, systems engineering, Linux systems administration, or a closely related technical field.\nDemonstrated hands-on experience operating, integrating, or sustaining systems connected to the DODIN, including familiarity with Department of Defense network access, security, configuration, and operational requirements.\nCurrent Department of Defense 8570-compliant certification appropriate to the assigned information assurance or cybersecurity workforce functions.\nDemonstrated hands-on experience deploying, administering, troubleshooting, and upgrading Kubernetes environments.\nDemonstrated hands-on experience with AWS infrastructure and services, including compute, networking, storage, identity, security, monitoring, and automation capabilities.\nExperience administering Linux-based systems and troubleshooting operating system, process, package, file system, permissions, networking, and performance issues.\nExperience building, securing, deploying, and operating containers using Docker, Open Container Initiative-compatible technologies, or equivalent container tooling.\nExperience with infrastructure as code, configuration automation, source control, continuous integration and continuous delivery pipelines, and repeatable deployment practices.\nWorking knowledge of enterprise networking concepts, including TCP/IP, routing, firewalls, Domain Name System, load balancing, virtual private networks, Transport Layer Security, certificates, and network segmentation.\nWorking knowledge of Department of Defense cybersecurity and authorization practices, including Risk Management Framework activities, Security Technical Implementation Guides, vulnerability management, continuous monitoring, and Authority to Operate requirements.\nAbility to independently diagnose complex technical problems, coordinate across multiple technical teams, document findings, and drive issues through resolution.\nStrong written and verbal communication skills, including the ability to explain technical issues, risks, and recommendations to engineering, cybersecurity, program, and mission stakeholders.\nAbility to work effectively in a remote environment, protect government information, maintain reliable connectivity, and travel periodically as required.\nDesired Qualifications:\nExperience operating Kubernetes on Amazon Elastic Kubernetes Service within AWS GovCloud or another Department of Defense-authorized cloud environment.\nExperience supporting systems at Department of Defense Impact Level 4, Impact Level 5, or Impact Level 6.\nExperience with Terraform, AWS CloudFormation, GitLab, GitHub Actions, Jenkins, Argo CD, Helm, Kustomize, or comparable platform engineering and GitOps tools.\nExperience with observability technologies such as Amazon CloudWatch, Prometheus, Grafana, OpenSearch, Elastic, Fluent Bit, or comparable logging and monitoring platforms.\nExperience with container security, software supply-chain controls, image scanning, software bills of materials, Iron Bank images, or hardened container baselines.\nExperience integrating platform services with Common Access Card authentication, Department of Defense public key infrastructure, identity providers, role-based access control, attribute-based access control, or Zero Trust architectures.\nExperience with service mesh, secrets management, policy as code, automated compliance, high availability, disaster recovery, or multi-account AWS architectures.\nAWS, Certified Kubernetes Administrator, Certified Kubernetes Application Developer, Linux, cybersecurity, or related professional certification.\nPrior experience directly supporting a Department of War mission partner, combatant command, military service component, Special Operations Forces organization, or other national security customer.\nTarget salary range: $135,000 - $230,000\nDisclaimer: The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.\nApplicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.\nJob Locations\nUS-Remote","description_format":"text","description_chars":9320,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":true,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Military","LLM & Generative AI","Creative Agencies","Information Security"],"lifecycle":[{"event":"open","at":"2026-09-30T00:44:32Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":9,"reasons":["conf:9","velocity","win:early","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":230000,"is_top_pay":true},"html_url":"https://alion.io/job/lmi-machine-learning-engineer","json_url":"https://alion.io/job/lmi-machine-learning-engineer.json","meta":{"generated_at":"2026-10-01T12:58:39Z","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":4489,"day_limit":5000,"remaining_today":511,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}