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Remote Director Machine Learning Jobs in Washington

Comcast

Engineer 6, Machine Learning, Data & AI

Reston, VA · On-site +1

$119K - $143K/yr

... remote option.) Job Summary We are seeking a visionary Senior Technologist, Data & Agentic AI ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Comcast

Engineer 6, Machine Learning, Data & AI

Washington, DC · On-site +1

$129K - $155K/yr

... remote option.) Job Summary We are seeking a visionary Senior Technologist, Data & Agentic AI ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Knexus

AI Software Engineer (Remote)

Vienna, VA · Remote

This role involves leveraging cutting-edge technologies, including GenAI and machine learning ... Our work has a direct, mission-driven impact, and we believe that our innovative ideas help us stay ...

West 4th Strategy

Data Scientist (Remote)

Washington, DC · On-site +1

$135K - $150K/yr

Build and implement machine learning models and/or predictive analytics. * Maintenance of ... Remote - Eastern Standard Time zone - preferred but not required CLEARANCE * U.S. Citizenship ...

Maximus

Data Scientist (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist (Remote) Date Tuesday, August 4, 2026 City ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

Sparibis

Azure Data Architect

Washington, DC · On-site +1

$72.25 - $92.75/hr

Location: 100% Remote. This is a United States based position, and candidates must reside in the ... Expertise in statistical modeling, machine learning algorithms, and data mining techniques. * Must ...

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Remote Director Machine Learning information

What does a remote director of machine learning do?

A Remote Director of Machine Learning leads teams of data scientists and engineers to develop, implement, and oversee machine learning solutions for an organization, all while working remotely. They are responsible for setting the strategic direction for ML projects, collaborating with stakeholders, and ensuring that models align with business objectives. This role typically involves both technical leadership—such as reviewing algorithms and architectures—and managerial duties, such as mentoring staff and managing budgets. Working remotely, they use digital collaboration tools to communicate, monitor progress, and deliver results effectively.

How does a remote director of machine learning typically coordinate and lead distributed teams across different time zones?

As a Remote Director of Machine Learning, effective coordination of distributed teams requires strong communication strategies, including regular video meetings, clear documentation, and use of collaborative project management tools. Leaders in this role often establish overlapping core hours and leverage asynchronous communication to accommodate various time zones. They focus on aligning goals, fostering a culture of transparency, and ensuring continuous progress through well-defined milestones. Building trust and maintaining team engagement remotely are common challenges, but successful directors prioritize mentorship, feedback, and virtual team-building activities to create a cohesive work environment.

What are the key skills and qualifications needed to thrive as a remote director of machine learning, and why are they important?

To thrive as a Remote Director of Machine Learning, you need advanced expertise in machine learning algorithms, data science, and leadership, typically supported by a graduate degree in a related field and extensive experience in deploying ML solutions. Familiarity with tools like Python, TensorFlow, PyTorch, cloud platforms, and experience with project management systems is essential, and certifications such as AWS Certified Machine Learning can be advantageous. Outstanding communication, strategic thinking, and the ability to mentor and manage distributed teams are crucial soft skills in this role. These skills and qualities are vital to successfully lead innovative ML projects, align technical teams with business goals, and drive impactful outcomes in a remote environment.

What is the difference between Remote Director Machine Learning vs Remote Data Science Manager?

AspectRemote Director Machine LearningRemote Data Science Manager
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related field; experience in ML algorithmsMaster's in Data Science, Statistics, or related; strong analytical background
Work EnvironmentLeads ML teams, develops models, and oversees deployment in tech-focused companiesManages data science teams, focuses on insights and analytics for business decisions
Employer & Industry UsageTech firms, AI startups, large enterprises with AI initiativesFinancial, healthcare, retail, and other industries leveraging data insights

While both roles require advanced education and involve data-driven work, the Remote Director Machine Learning primarily focuses on leading ML model development and deployment, whereas the Remote Data Science Manager emphasizes managing data analysis teams and deriving business insights.

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

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

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

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

What cities in Washington are hiring for Remote Director Machine Learning jobs?

Cities in Washington with the most Remote Director Machine Learning job openings:

Remote Director Machine Learning jobs near you

Engineer 6, Machine Learning, Data & AI

Comcast

Reston, VA • On-site, Remote

$119K - $143K/yr

Full-time

Posted 12 days ago

Job description

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You'll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Job Summary

We are seeking a visionary Senior Technologist, Data & Agentic AI Enablement to shape the future of our enterprise data ecosystem and accelerate the next generation of AI-driven experiences. This enterprise leadership role is responsible for two complementary missions:
Preparing enterprise data for an Agentic AI future, ensuring data is trusted, discoverable, semantically rich, governed, and consumable by AI agents. Transforming data engineering through Agentic AI, embedding AI across the data engineering lifecycle to improve productivity, quality, reliability, and speed of delivery. The successful candidate will define the architecture, standards, and engineering patterns that enable AI to become an active participant in the design, development, testing, operation, and optimization of enterprise data platforms. This highly influential role partners closely with Data Engineering, Data Platforms, Enterprise Architecture, Security, Product, and AI teams to accelerate data modernization and AI-enabled business transformation.

Job Description

Agentic AI Transformation of Data Engineering:

Lead the strategy for integrating Agentic AI across the enterprise data engineering lifecycle, enabling AI-assisted development, operations, and platform management.

Responsibilities include:

  • Define the enterprise roadmap for incorporating AI agents into data engineering workflows, platform operations, and software delivery.
  • Partner with platform engineering teams to integrate AI capabilities into CI/CD, Infrastructure-as-Code (IaC), and DevSecOps practices.
  • Evaluate emerging agent frameworks, copilots, and autonomous engineering platforms for enterprise adoption.
  • Establish best practices and governance for AI-assisted engineering and operational processes.
Enterprise Data Strategy for AI & Agentic Systems:

Develop and drive the enterprise strategy for preparing data assets to support AI, Generative AI, and Agentic AI use cases.

Responsibilities include:

  • Define principles and reference architectures that enable AI agents to discover, access, understand, and act upon enterprise data safely and effectively.
  • Partner with business and technology leaders to identify high-value opportunities for Agentic AI solutions.
  • Establish enterprise standards that align data, AI, and business strategies.
Data Architecture & AI Readiness

Lead architectural efforts to ensure enterprise data is optimized for both human and AI consumption.

Responsibilities include:

  • Establish standards that ensure data is:
    • Discoverable
    • Well-described and semantically rich
    • Governed and trusted
    • Accessible through standardized interfaces
    • Consumable by both people and AI agents
  • Drive adoption of metadata-driven architectures, semantic models, knowledge graphs, and business ontologies.
  • Ensure enterprise data products support machine-to-machine interactions in addition to traditional analytics use cases.
Agentic Data Enablement:

Define the frameworks that enable AI agents to effectively interact with enterprise data and knowledge assets.

Responsibilities include:

  • Establish standards for exposing enterprise data through APIs, semantic layers, data products, and retrieval systems.
  • Partner with platform teams to develop capabilities supporting:
    • Retrieval-Augmented Generation (RAG)
    • Agent orchestration platforms
    • Tool and API discovery
    • Vector-based retrieval architectures
    • Context management and memory frameworks
  • Develop patterns that allow AI agents to access enterprise knowledge securely and responsibly.
Data Governance & Trust:

Ensure governance and trust frameworks evolve to support autonomous and AI-assisted decision making.

Responsibilities include:

  • Establish controls for data lineage, provenance, quality, explainability, and auditability.
  • Partner with Security, Privacy, and Risk teams to implement responsible AI controls and secure data access practices.
  • Define trust frameworks that enable AI agents to operate within approved business guardrails.
Semantic Layer & Knowledge Management:

Drive the development of enterprise semantic capabilities that improve data accessibility and AI reasoning.

Responsibilities include:

  • Lead development of enterprise semantic models and shared business definitions.
  • Improve metadata quality, business context, and knowledge accessibility across the organization.
  • Advance enterprise knowledge management practices that enhance AI reasoning, discovery, and decision support.
Platform & Ecosystem Alignment:

Collaborate across teams to ensure enterprise platforms support AI-native consumption patterns.

Responsibilities include:

  • Partner with Data Platform, Engineering, Analytics, and Product teams to align technology roadmaps.
  • Collaborate with BI and analytics teams to maintain consistent business metrics and semantic definitions across human and AI consumers.
  • Influence technology investments that enable future AI and Agentic AI capabilities.
Innovation & Thought Leadership

Serve as a strategic thought leader on AI readiness, data modernization, and enterprise architecture.

Responsibilities include:

  • Monitor emerging trends in AI, Agentic Systems, Data Architecture, and Knowledge Management.
  • Evaluate innovative technologies and identify strategic adoption opportunities.
  • Advise executive leadership on enterprise AI strategy and future-state architecture.
Qualifications
  • + years of experience in Data Architecture, Data Engineering, Enterprise Architecture, or related technology disciplines.
  • Proven experience designing and scaling enterprise data ecosystems.
  • Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.
  • Demonstrated success influencing outcomes across large, matrixed organizations.
Technical Expertise
  • Deep understanding of modern data architectures, including data warehouses, data lakes, lakehouses, and data mesh concepts.
  • Expertise in metadata management, semantic modeling, data governance, and data product design.
  • Strong understanding of APIs, event-driven architectures, and interoperability standards.
  • Experience with AI technologies, including LLMs, RAG architectures, vector databases, agent frameworks, and AI orchestration platforms.
  • Knowledge of modern software engineering, DevSecOps, CI/CD, and cloud-native architectures.
Leadership & Communication
  • Strong executive communication and stakeholder management skills.
  • Ability to translate emerging technologies into practical enterprise strategies.
  • Proven ability to lead through influence across business and technology organizations.
  • Demonstrated thought leadership in data, AI, or enterprise architecture domains.
Preferred Candidate Profile :

A strategic technology leader with deep expertise in enterprise data architecture and a passion for advancing AI adoption. This individual combines strong technical vision, architectural leadership, and business acumen to help the organization build a trusted, AI-ready data foundation while transforming the way engineering teams work through Agentic AI.

Disclaimer:

This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.

Skills

Agentic AI, AI Adoption, Data Architecture Development, Data Engineering, Data Strategies, Enterprise Data

Compensation

This job can be performed in Virginia, and District of Columbia with a Pay Range of $224,190.44 - $351,571.37Comcast intends to offer the selected candidate base pay within this range, dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.

Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.

Education

Bachelor's DegreeWhile possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.

Certifications (if applicable)

Relevant Work Experience

15 Years +Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.

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