{"schemaVersion":"jobsearcher.job.v1","id":"2dca4952af048c847e7d4313","url":"https://jobsearcher.com/jobs/2dca4952af048c847e7d4313","canonicalUrl":"https://jobsearcher.com/jobs/2dca4952af048c847e7d4313","title":"Machine Learning Engineer","description":"Eligibility\r\nU.S. citizenship required; all work must be conducted within the continental U.S.\r\nWho we are\r\nRaft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.\r\nAbout the role\r\nAs Lead AI/ML Software Engineer for [R]AIMS, you will serve as a senior technical leader responsible for evolving the architecture, execution, and engineering rigor of Raft's AI Mission System. You will be hands-on in the codebase, leading by doing, while setting technical direction and raising the quality of engineering across the team.\r\nYou will partner closely with platform leadership, product, and delivery teams to drive architectural decisions, lead major technical epics from conception through delivery, and establish the engineering patterns that the platform will grow on. You will operate at the intersection of distributed systems, AI/ML platform engineering, Kubernetes-native infrastructure, and data-intensive application development, balancing rapid mission delivery with long-term platform integrity.\r\nThis role requires someone equally comfortable writing production systems with complex multi-vendor integrations, debugging difficult distributed systems issues, leading design reviews, and making pragmatic tradeoff decisions under ambiguity.\r\nWhat you'll do\r\nDrive architectural decisions across the [R]AIMS platform, evaluating tradeoffs across performance, scalability, security, and maintainability and building alignment across engineering and product stakeholders\r\nLead major technical epics from conception through delivery, decomposing ambiguous problems into executable plans and keeping cross-functional teams moving with clarity and momentum\r\nSimplify and rationalize distributed system architecture as the platform scales, reducing incidental complexity and improving operational reliability without sacrificing capability\r\nOptimize platform performance across both edge and cloud deployment targets, identifying and resolving bottlenecks in data-intensive, latency-sensitive operational environments\r\nEstablish strong engineering foundations and reusable technical patterns that improve developer productivity and code quality across the team\r\nMentor engineers at multiple levels, conducting design reviews, providing substantive code feedback, and actively elevating technical execution across the platform\r\nPartner with AI/ML engineers on model integration, inference optimization, and the operational deployment of agentic workflows within [R]AIMS\r\nEngage directly with customers and program stakeholders at operationally demanding environments across the Department of Defense, representing Raft's technical capabilities with credibility and clarity\r\nWhat we are looking for\r\n6+ years of hands-on experience building and shipping production software systems across the full stack (frontend, backend, infrastructure, and ML)\r\nDeep software engineering fundamentals with demonstrated ability to design, build, and evolve complex systems that perform reliably at scale\r\nExceptional technical communication skills; able to lead through influence across engineering, product, and leadership stakeholders without requiring direct authority\r\nProven experience designing and evolving distributed systems, including service decomposition, inter-service communication patterns, fault tolerance, and observability\r\nStrong hands-on experience with Kubernetes and cloud-native platform architecture in production environments\r\nExperience building data-intensive or AI-enabled production systems with real operational users and real performance constraints\r\nDemonstrated technical leadership over large, cross-functional engineering initiatives with clear ownership and accountability for outcomes\r\nStrong system design and architecture decision-making ability, with a track record of making the right call under incomplete information\r\nSome experience or exposure to training, fine-tuning, or deploying machine learning models in production contexts\r\nAbility to obtain Security+ certification within the first 90 days of employment\r\nUS citizenship required; ability to obtain and maintain a Top Secret/SCI clearance\r\nHighly preferred\r\nExperience building AI/ML infrastructure or agentic systems, including orchestration frameworks, tool-use patterns, and LLM integration in production\r\nExperience with streaming and event-driven architectures, particularly Kafka, Kafka Streams, or Apache Flink\r\nExperience with platform engineering and internal developer tooling, including golden-path frameworks, shared libraries, and developer experience improvements\r\nExperience with real-time inference or operational AI systems in latency-sensitive environments\r\nExperience building secure, compliant systems for regulated or mission-critical environments, including familiarity with IL4/IL5/IL6 requirements or RMF processes\r\nPrior work in defense, national security, or classified program environments\r\nActive clearance preferred\r\nWhat Success Looks Like\r\n[R]AIMS has a coherent, well-documented architecture that engineers at all levels understand and can contribute to confidently\r\nMajor platform initiatives ship on time with high engineering quality, low rework rates, and clear technical rationale behind key decisions\r\nThe engineering team is measurably stronger because of your presence: better design reviews, sharper code, cleaner systems\r\nCustomers trust Raft technically. When you're in the room, they leave the conversation with confidence in what we're building and how we're building it\r\nPlatform complexity is decreasing relative to capability, not increasing\r\nClearance Requirements\r\nNo clearance required to start\r\nMust be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance preferred\r\nSalary Range\r\n$180,000.00 – $230,000.00\r\nWork Type\r\nRemote within the U.S.; preference for candidates located near a Raft hub (McLean, VA; Colorado Springs, CO; Tacoma, WA; Oahu, HI, Tampa, FL; Boston, MA)\r\nUp to 25% travel\r\nWhat we will offer you\r\nHighly competitive salary\r\nFully covered healthcare, dental, and vision coverage\r\n401(k) and company match\r\nTake as you need PTO + 11 paid holidays\r\nEducation & training benefits\r\nGenerous Referral Bonuses\r\nAnd More!\r\nEqual Opportunity Employer\r\nWe're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.\r\nJ-18808-Ljbffr","company":"Raft","rawCompany":"raft","city":"McLean","state":"VA","isRemote":false,"isActive":true,"createdAt":"2026-08-08T01:30:07.738Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Eligibility\r\nU.S. citizenship required; all work must be conducted within the continental U.S.\r\nWho we are\r\nRaft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.\r\nAbout the role\r\nAs Lead AI/ML Software Engineer for [R]AIMS, you will serve as a senior technical leader responsible for evolving the architecture, execution, and engineering rigor of Raft's AI Mission System. You will be hands-on in the codebase, leading by doing, while setting technical direction and raising the quality of engineering across the team.\r\nYou will partner closely with platform leadership, product, and delivery teams to drive architectural decisions, lead major technical epics from conception through delivery, and establish the engineering patterns that the platform will grow on. You will operate at the intersection of distributed systems, AI/ML platform engineering, Kubernetes-native infrastructure, and data-intensive application development, balancing rapid mission delivery with long-term platform integrity.\r\nThis role requires someone equally comfortable writing production systems with complex multi-vendor integrations, debugging difficult distributed systems issues, leading design reviews, and making pragmatic tradeoff decisions under ambiguity.\r\nWhat you'll do\r\nDrive architectural decisions across the [R]AIMS platform, evaluating tradeoffs across performance, scalability, security, and maintainability and building alignment across engineering and product stakeholders\r\nLead major technical epics from conception through delivery, decomposing ambiguous problems into executable plans and keeping cross-functional teams moving with clarity and momentum\r\nSimplify and rationalize distributed system architecture as the platform scales, reducing incidental complexity and improving operational reliability without sacrificing capability\r\nOptimize platform performance across both edge and cloud deployment targets, identifying and resolving bottlenecks in data-intensive, latency-sensitive operational environments\r\nEstablish strong engineering foundations and reusable technical patterns that improve developer productivity and code quality across the team\r\nMentor engineers at multiple levels, conducting design reviews, providing substantive code feedback, and actively elevating technical execution across the platform\r\nPartner with AI/ML engineers on model integration, inference optimization, and the operational deployment of agentic workflows within [R]AIMS\r\nEngage directly with customers and program stakeholders at operationally demanding environments across the Department of Defense, representing Raft's technical capabilities with credibility and clarity\r\nWhat we are looking for\r\n6+ years of hands-on experience building and shipping production software systems across the full stack (frontend, backend, infrastructure, and ML)\r\nDeep software engineering fundamentals with demonstrated ability to design, build, and evolve complex systems that perform reliably at scale\r\nExceptional technical communication skills; able to lead through influence across engineering, product, and leadership stakeholders without requiring direct authority\r\nProven experience designing and evolving distributed systems, including service decomposition, inter-service communication patterns, fault tolerance, and observability\r\nStrong hands-on experience with Kubernetes and cloud-native platform architecture in production environments\r\nExperience building data-intensive or AI-enabled production systems with real operational users and real performance constraints\r\nDemonstrated technical leadership over large, cross-functional engineering initiatives with clear ownership and accountability for outcomes\r\nStrong system design and architecture decision-making ability, with a track record of making the right call under incomplete information\r\nSome experience or exposure to training, fine-tuning, or deploying machine learning models in production contexts\r\nAbility to obtain Security+ certification within the first 90 days of employment\r\nUS citizenship required; ability to obtain and maintain a Top Secret/SCI clearance\r\nHighly preferred\r\nExperience building AI/ML infrastructure or agentic systems, including orchestration frameworks, tool-use patterns, and LLM integration in production\r\nExperience with streaming and event-driven architectures, particularly Kafka, Kafka Streams, or Apache Flink\r\nExperience with platform engineering and internal developer tooling, including golden-path frameworks, shared libraries, and developer experience improvements\r\nExperience with real-time inference or operational AI systems in latency-sensitive environments\r\nExperience building secure, compliant systems for regulated or mission-critical environments, including familiarity with IL4/IL5/IL6 requirements or RMF processes\r\nPrior work in defense, national security, or classified program environments\r\nActive clearance preferred\r\nWhat Success Looks Like\r\n[R]AIMS has a coherent, well-documented architecture that engineers at all levels understand and can contribute to confidently\r\nMajor platform initiatives ship on time with high engineering quality, low rework rates, and clear technical rationale behind key decisions\r\nThe engineering team is measurably stronger because of your presence: better design reviews, sharper code, cleaner systems\r\nCustomers trust Raft technically. When you're in the room, they leave the conversation with confidence in what we're building and how we're building it\r\nPlatform complexity is decreasing relative to capability, not increasing\r\nClearance Requirements\r\nNo clearance required to start\r\nMust be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance preferred\r\nSalary Range\r\n$180,000.00 – $230,000.00\r\nWork Type\r\nRemote within the U.S.; preference for candidates located near a Raft hub (McLean, VA; Colorado Springs, CO; Tacoma, WA; Oahu, HI, Tampa, FL; Boston, MA)\r\nUp to 25% travel\r\nWhat we will offer you\r\nHighly competitive salary\r\nFully covered healthcare, dental, and vision coverage\r\n401(k) and company match\r\nTake as you need PTO + 11 paid holidays\r\nEducation & training benefits\r\nGenerous Referral Bonuses\r\nAnd More!\r\nEqual Opportunity Employer\r\nWe're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.\r\nJ-18808-Ljbffr","datePosted":"2026-08-08T01:30:07.738Z","dateModified":"2026-08-08T01:30:07.738Z","hiringOrganization":{"@type":"Organization","name":"Raft","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"McLean","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"2dca4952af048c847e7d4313"},"url":"https://jobsearcher.com/jobs/2dca4952af048c847e7d4313"}}