Principal MLOps Engineer

This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.Who we are:Raft ( 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.We're looking for an experienced Principal ML OpsEngineer to support our customers and join our passionate team of high-impact problem solvers.About the role: Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.In this role, you will help design, deploy, and mature Raft's ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.What you'll do:Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systemsHelp mature Raft's internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational supportDeploy and manage machine learning workloads on Kubernetes, including GPU-enabled clustersSupport model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systemsBuild and maintain CI/CD workflows for ML services, model artifacts, and platform componentsPartner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deploymentImprove observability, reliability, security, and maintainability across ML infrastructure and servicesHelp evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloadsContribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environmentsSupport compliance-driven deployment practices and secure software supply chain requirements in defense environmentsGet hands-on with customers at the most forward-leaning places in the Department of WarWhat we are looking for:7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles5+ years of experience with Docker and Kubernetes in production environments5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environmentsStrong experience provisioning, operating, and troubleshooting Kubernetes clusters in productionExperience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teamsPractical experience deploying machine learning workloads on KubernetesExperience managing clusters or workloads that use GPUsStrong understanding of Helm and Kubernetes deployment patternsStrong scripting or programming skills, preferably in PythonExperience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflowsStrong troubleshooting, systems thinking, and communication skillsAbility to work independently and collaboratively in a fast-moving environmentAbility to obtain and maintain a Top Secret clearanceAbility to obtain Security+ certification within the first 90 days of employmentHighly preferred:Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologiesExperience with secure and compliant deployment practices in regulated or government environmentsExperience with Kubernetes-based ML platforms such as KubeflowFamiliarity with service mesh technologies such as IstioExperience provisioning and debugging complex CI/CD systemsExperience with infrastructure as code tools such as TerraformFamiliarity with software supply chain security, container hardening, vulnerability management, and runtime scanningExperience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edgeBackground working with machine learning engineers on model training, evaluation, packaging, and release workflowsFamiliarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog systemWhat success looks like:You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in productionML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to useModel deployments become more secure, observable, and supportable across real-world mission environmentsThe organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownershipClearance Requirements:Ability to obtain and maintain a Top Secret clearanceWork Type:Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLYMay require up to 40% travelSalary Range: $150,000.00 - $200,000.00What we will offer you: Highly competitive salaryFully covered healthcare, dental, and vision coverage401(k) and company matchTake as you need PTO + 11 paid holidaysEducation & training benefitsAnnual budget for your tech/gadgets needsMonthly box of yummy snacks to eat while doing meaningful workRemote, hybrid, and flexible work optionsTeam off-site in fun places!Generous Referral BonusesAnd More!Our Vision Statement:We bridge the gap between humans and data through radical transparency and our obsession withthemission.Our Customer Obsession:We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.How do we get there?Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking,and collaboration is a norm.Raft's core philosophy isUbuntu: IAm, BecauseWe are. We support our"nadi"by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.We'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.