Raft Company Website

Role Description 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 systems - Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support - Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters - Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems - Build and maintain CI/CD workflows for ML services, model artifacts, and platform components - Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment - Improve observability, reliability, security, and maintainability across ML infrastructure and services - Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads - Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments - Support compliance-driven deployment practices and secure software supply chain requirements in defense environments - Get hands-on with customers at the most forward-leaning places in the Department of War Qualifications - 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles - 5+ years of experience with Docker and Kubernetes in production environments - 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments - Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production - Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams - Practical experience deploying machine learning workloads on Kubernetes - Experience managing clusters or workloads that use GPUs - Strong understanding of Helm and Kubernetes deployment patterns - Strong scripting or programming skills, preferably in Python - Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows - Strong troubleshooting, systems thinking, and communication skills - Ability to work independently and collaboratively in a fast-moving environment - Ability to obtain and maintain a Top Secret clearance - Ability to obtain Security+ certification within the first 90 days of employment Highly preferred: - Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies - Experience with secure and compliant deployment practices in regulated or government environments - Experience with Kubernetes-based ML platforms such as Kubeflow - Familiarity with service mesh technologies such as Istio - Experience provisioning and debugging complex CI/CD systems - Experience with infrastructure as code tools such as Terraform - Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning - Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge - Background working with machine learning engineers on model training, evaluation, packaging, and release workflows - Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system What success looks like: - You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production - ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use - Model deployments become more secure, observable, and supportable across real-world mission environments - The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership Clearance Requirements: - Ability to obtain and maintain a Top Secret clearance Work Type: - Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI - May require up to 40% travel Salary Range: $150,000.00 - $200,000.00 What we will offer you: - Highly competitive salary - Fully covered healthcare, dental, and vision coverage - 401(k) and company match - Take as you need PTO + 11 paid holidays - Education & training benefits - Annual budget for your tech/gadgets needs - Monthly box of yummy snacks to eat while doing meaningful work - Remote, hybrid, and flexible work options - Team off-site in fun places! - Generous Referral Bonuses - And More!

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 (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. We’re looking for an AI/ML Engineer to support our customers and join our passionate team of high-impact problem solvers. About the role: In your role as an AI/ML Engineer, you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers. What we are looking for: - 3+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application - Practical experience in Machine Learning models and Software Engineering - A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams - Experience building and maintaining machine learning platforms and pipelines - Experience in building machine learning models, and - Experience in using data processing frameworks (Apache Spark preferred) - Practical programming and scripting skills (Python preferred) - Fast learner, analytical thinker, creative, hands-on, strong communication skills - Able to work both independently and as part of a team - Excellent problem-solving skills and attention to detail. - Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps - Obtain Security+ within the first 90 days of employment with Raft Highly preferred: - PhD graduate - Publications or GitHub repos showcasing your skills Clearance Requirements: - Ability to obtain a Top Secret clearance with potential for SCI Salary: - $110,000-$165,000 - The determination of compensation is predicated upon a candidate's comprehensive experience, demonstrated skill, and proven abilities Work Type: - Can work remotely from any of the following locations: Tampa FL, Hanscom AFB, Colorado Springs CO, San Diego CA, Tacoma WA, NCR (DC) - May require up to 35% travel What we will offer you: - Highly competitive salary - Fully covered healthcare, dental, and vision coverage - 401(k) and company match - Take as you need PTO + 11 paid holidays - Education & training benefits - Annual budget for your tech/gadgets needs - Generous Referral Bonuses - And More! Our Vision Statement: We bridge the gap between humans and data through radical transparency and our obsession with the mission. 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 is Ubuntu: I Am, Because We 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.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description You will be part of the team building a data focused product that is built on best of breed open source solutions like Kafka, Trino, DuckDB, and Superset. You will work both on backend and frontend to build end-to-end features that make interacting with data easier enabling users to be able to tell a data story through our product. Qualifications - 8+ Years of experience building RESTFul APIs to take concept to implementation in one of the following languages: Go (preferred), Java, Python, Rust (nice to have), and Scala - 5+ Years of experience in frontend frameworks like React with a focus on Typescript or Javascript - Deep design of software design and architecture - Experience with large-scale relational and non-relational databases such as PostgreSQL, MySQL, MongoDB, and Elasticsearch to handle low-latency requirements - Experience with building and releasing software in cloud-native environments - Experience using a variety of package managers/dependency managers including Maven, Gradle, and NPM - Experience with Docker and Kubernetes, including containerizing solutions and working with distributed clusters - Experience working with AI coding assistants (e.g., Claude Code) - Demonstrated ability to take on large responsibilities and own complex work or project lifecycles - STEM Background or relevant industry experience - Able to obtain Security+ certification within 90 days of employment with Raft Requirements - Highly preferred: Experience with Kafka or RabbitMQ - Highly preferred: Experience with Delta Lake - Highly preferred: Experience with AWS or Azure - Ability to obtain and maintain a Top Secret security clearance - Remote work (candidates based in DMV/NCR, Tampa, Dayton, OH; or Hawaii strongly preferred) - May require up to 25% travel Benefits - Highly competitive salary - Fully covered healthcare, dental, and vision coverage - 401(k) and company match - Take as you need PTO + 11 paid holidays - Education & training benefits - Team off-site in fun places! - Generous Referral Bonuses - And More!