Director of Machine Learning
Posted 3 days ago
virtualiticsWashington (DC)
Data ScientistsComputer Systems Design Services
SENIORITY
Manager
About the role
Director of Machine Learning Engineering (Secret Cleared, DMV) About Virtualitics: Virtualitics is a fast-growing, Caltech-born defense tech company (:120 people) dedicated to reversing the decline in military readiness. Virtualitics builds AI-native readiness intelligence for the US and allied nations’ defense sector. Virtualitics Iris transforms how defense organizations act on maintenance, logistics, personnel, and global force management data. Our team is actively refining agentic workflows, composable AI agents, and generative interfaces to replace static dashboards with dynamic, conversational intelligence.
What You Will Do: Lead the Machine Learning Engineering team
Provide guidance on how to architect robust, scalable applications using sound engineering principles, managing the complete data lifecycle from acquisition to model inference and postprocessing
Tackle runtime performance and optimize data access patterns for highly responsive applications
Collaborate across the delivery team (e.g. Product, Customer Success, Dev Ops, and QA) to align engineering deliverables with strategic customer commitments
Tackle key issues across Delivery and Platform teams and flag pain points to help influence the roadmap
Set the technical hiring bar and mentor engineers, ensuring teams are well-staffed and capable
Clearly communicate technical progress, risks, and ROI, directly linking AI team output to revenue, mission impact both up and down as well as internally and externally
Core Requirements: Clearance & Location: Must hold at least a U.S. Secret security clearance and be willing to upgrade to a TS/SCI if needed. Must be willing to travel to customer locations as needed
Engineering Fundamentals: A degree in Computer Science or related field and 8+ years of software engineering experience. We target candidates with a strong background in software engineering and production deployment, rather than strictly research-oriented backgrounds
AI & Systems: A proven track record of deploying software into production environments. Has shipped production-grade AI / agentic systems
GPU Fluency: Has experience with offloading compute for AI systems to GPUs and is comfortable with designing training and inference pipelines
Full Stack & Dev Sec Ops: Understands full stack software development, Dev Sec Ops, and AI systems holistically. Familiarity with Docker, Kubernetes, and Git
Data Ecosystem: Proficiency in Python with a solid understanding of the Python Data Stack (pandas, Num Py, scikit-learn, PyTorch, Matplotlib, etc.). Experience working with a wide variety of data (both structured and unstructured) from different sources
Culture & Values: Embody Virtualitics core values by bringing a positive attitude, fostering a highly collaborative environment, and always being ready to "lean in" to tackle complex challenges alongside the team
Preferred Qualifications (Pluses): Has built and cultivated a high functioning Machine Learning Engineering team before
Has contributed to building engineering excellence and has top-tier engineering experience
Experience with big data technologies and frameworks (Spark, Databricks, Snowflake, etc.)
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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