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Director Learning Technology Jobs in Washington (NOW HIRING)

Beyond SOF

Director of IT

Arlington, VA · On-site

Director of IT Location: Remote (candidate needs to be based in the US preferably CONUS) Reports to ... Demonstrated success in integrating AI, machine learning, or agentic tools (e.g., autonomous agents ...

Howard Community College

Learning Designer

Columbia, MD · On-site

$35/hr

... Director, Center for Learning Excellence (CLE) and works closely with CLE and Workforce, Career ... Train and mentor to faculty and staff in technology and instructional design best practices

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Director Learning Technology information

What does a director learning technology do?

A Director of Learning Technology oversees the strategic implementation of technology to enhance learning and development within an organization. They evaluate, select, and manage learning management systems (LMS), e-learning tools, and other digital resources to support employee training or educational initiatives. This role involves collaborating with stakeholders to align technology with learning objectives, ensuring an engaging and effective learning experience. Additionally, they monitor industry trends to adopt innovative solutions that improve learning outcomes.

What are the typical day-to-day responsibilities of a director learning technology?

As a Director Learning Technology, your daily tasks often include overseeing the planning and implementation of digital learning initiatives, collaborating with educators and IT teams to select or optimize learning platforms, and analyzing usage data to ensure effectiveness. You’ll lead teams of instructional designers and technologists, manage project timelines and budgets, and stay updated on emerging educational technologies. Regular meetings with department heads, vendor negotiations, and staff training sessions are also common. This role requires a balance of high-level strategy and hands-on problem-solving to ensure that technology enhances educational outcomes.

What are the key skills and qualifications needed to thrive in the director learning technology position, and why are they important?

To thrive as a Director Learning Technology, you need expertise in instructional design, educational technology, curriculum development, and leadership, typically supported by an advanced degree in education or a related field. Familiarity with learning management systems (LMS), authoring tools, data analytics platforms, and certifications in project management or instructional design are highly valuable. Strategic thinking, effective communication, and strong change management abilities are key soft skills for this role. These skills ensure successful technology integration, drive learning innovation, and align educational solutions with organizational goals.

What are the most commonly searched types of Learning Technology jobs in Washington?

The most popular types of Learning Technology jobs in Washington are:

What are popular job titles related to Director Learning Technology jobs in Washington?

For Director Learning Technology jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Director Learning Technology jobs in Washington look for?

The top searched job categories for Director Learning Technology jobs in Washington are:

What cities in Washington are hiring for Director Learning Technology jobs?

Cities in Washington with the most Director Learning Technology job openings:

Director Learning Technology jobs near you
Infographic showing various Director Learning Technology job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 14% Part Time, 2% Temporary, and 8% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Director of Machine Learning (Washington)

Washington, DC • On-site

Virtualitics
Software Development • 51 - 200 employees
Learn more about Virtualiticsexternal

Full-time

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Lead the Machine Learning Engineering team and oversee the development of AI-native readiness intelligence applications.

  • Provide guidance on architecting robust, scalable applications and managing the complete data lifecycle from acquisition to model inference and postprocessing.

  • Collaborate with cross-functional teams to align engineering deliverables with strategic customer commitments and communicate technical progress, risks, and ROI.

Job description

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, DevOps, 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 & DevSecOps: Understands full stack software development, DevSecOps, 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, NumPy, 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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