Senior Machine Learning Engineer

Build, Deploy, and Maintain AI for an Unpredictable World Ironwood Digital helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Ironwood Digital set out to make the journey from deployment to ongoing optimization simple and effective. With Ironwood Digital, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Ironwood Digital meets these demands—increasing reliability and performance while lowering costs and enabling confident, data-driven decision-making in dynamic environments. The Role As a Senior Machine Learning Engineer at Ironwood Digital, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer-driven projects and the enduring products of the company. You will be a key Ironwood Digital representative and technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Ironwood Digital’ core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities. You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome-driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all critical to success. Your day-to-day will include: Working with customers, engineers, and other stakeholders to define clear requirements that solve customers’ problems and leverage the capabilities of our AIOps platform Developing machine learning models and custom analytics that are applied to image, video, text, geospatial, time series, and structured data Orchestrating and automating complex data engineering and analytic pipelines Envisioning, specifying, and, at times, designing and implementing core product functionality Opportunities to conduct mission-critical field work This position follows a hybrid work model, combining remote work with on-site support at customer locations in the Northern Virginia area, with up to 10% travel. The Right Fit In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. We value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results. Here’s what we’re looking for: A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, other production analytics) Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala) Proficiency with modern software engineering tools and processes (e.g., Agile, version control, issue tracking, CI/CD, debugging) Active Secret (or above) US security clearance Due to the nature of this role, candidates must have US citizenship The Wish List We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of: Active TS/SCI security clearance Graduate degree in data science, machine learning, computer science, or a related discipline Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular) Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], infrastructure as code, major cloud architectures) Experience with a variety of unstructured data types (e.g., imagery, full motion video, text, acoustic, sonar, RF, telemetry signals) Experience with anomaly detection in