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Machine Learning Scientist Jobs in Washington, DC

Machine Learning Engineer

Alexandria, VA ยท Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Data Scientist Support - Consultative support for specialized workforce research & HR analytics. RESPONSIBILITIES AND DUTIES - Machine Learning Engineer | Data Management & Business Intelligence ...

Machine Learning Engineer

Alexandria, VA ยท Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Data Scientist. We seek Machine Learning Engineer | Human Capital Technology Support - Intelligent Automation (AI & RPA) [NSF0057057] candidates with relevant Government And Public Services Sector ...

Machine Learning Engineer

Reston, VA ยท On-site

$110 - $170/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Machine Learning Engineer

Chantilly, VA ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

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Showing results 1-20

Machine Learning Scientist information

See Washington, DC salary details

$84.3K

$152.9K

$214.2K

How much do machine learning scientist jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning scientist in Washington, DC is $152,909.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,597.00 and $170,175.00 per year, depending on experience, location, and employer.

What is a machine learning scientist?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What does a machine learning scientist do?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What skills and qualifications are needed to be a machine learning scientist?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

Is machine learning a high paying job?

Machine Learning Scientists typically earn high salaries due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python and TensorFlow. Salaries vary by industry, experience, and location but are generally above average compared to many other tech roles.

What are the most commonly searched types of Machine Learning Scientist jobs in Washington, DC?

The most popular types of Machine Learning Scientist jobs in Washington, DC are:

Infographic showing various Machine Learning Scientist job openings in Washington, DC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $152,909 per year, or $73.5 per hour.

Senior Machine Learning Scientist, Agentic AI & GenAI Systems (Growth Marketing)

Traveltechessentialist

Washington, DC โ€ข On-site

$173 - $243/hr

Other

Medical, Dental, Vision, PTO

Posted yesterday

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Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Sr. Machine Learning Scientist, Agentic AI & GenAI Systems (Growth Marketing)

We create and deliver tailored marketing strategies for Expedia Groupโ€™s brands, focusing on establishing strong connections and cohesive experiences for travelers and partners. We leverage our functional expertise and creative excellence to build trust and loyalty for our brands through innovative marketing approaches and technology.

Our Growth Marketing team is redefining how AI-driven, agentic automation meets data-powered marketing. We build production-ready multimodal LLMs, GenAI, and agentic architectures that power personalized travel discovery, real-time cross-platform campaign execution, and interactive chatbots/UIs. For example, โ€œTrip Matchingโ€ on Instagram transforms inspiring reels and posts into instant hotel recommendations, powered entirely by our production AI.

We are looking for a handsโ€‘on Senior Machine Learning Scientist who thrives on building endโ€‘toโ€‘end systems, from backend architecture to userโ€‘facing interfaces, including agentic UX/UI, observability, and product integration.

In this role, you will:
  • Architect, build, and ship enterpriseโ€‘scale GenAI, RAG, and multiโ€‘agent systems endโ€‘toโ€‘end, including frontend, backend, and user interfaces.
  • Design hierarchical multiโ€‘agent ecosystems with Interactive Generative UIs, dashboards, and safety/observability features (e.g., UI is generated onโ€‘theโ€‘fly by an agent in response to what the user need).
  • Develop memory architectures: shortโ€‘term contextual memory, longโ€‘term episodic memory, knowledge graph augmentation, and adaptive retrieval systems.
  • Lead handsโ€‘on implementation of RAG pipelines, vector memory systems, and agent orchestration frameworks (LangChain, LangSmith, AutoGen, OpenAI/Claude Agents SDK, etc) and advanced evaluation platforms leveraging LLMโ€‘asโ€‘aโ€‘Judge, synthetic data generation, and agent trajectory assessment.
  • Train, fineโ€‘tune, adapt (LoRA/QLoRA/adapters), and distill LLMs, including RLHF/DPO, for productionโ€‘ready chatbots and GenAI products.
  • Build multimodal pipelines integrating vision, audio, text, and structured data, optimizing for scalability and latency.
  • Build and deploy largeโ€‘scale behavioral embedding systems that learn traveler representations from billions of search, booking, web, app, loyalty, and marketing interactions, leveraging distributed representation learning and realโ€‘time serving to power personalization, audience targeting, propensity models, and nextโ€‘bestโ€‘action recommendations.
  • Collaborate with product, and engineering teams to create intuitive, userโ€‘friendly interfacesand ensure seamless endโ€‘toโ€‘end user experiences.
  • Mentor engineers and ML scientists, set technical standards, conduct design reviews, and contribute to the organizationโ€™s technical maturity.
  • Represent the Org externally via openโ€‘source contributions, patents, conferences, and publications.
Experience and Qualifications:
  • 10+ years in software engineering, ML, and AI systems, with production GenAI deployments.
  • Deep expertise in LLM training, adaptation, distillation, RLHF/DPO, and RAG systems.
  • Solid foundation in NLP and experience with multimodal AI systems (visionโ€‘language models)
  • Proven experience building and operating multiโ€‘agent AI platforms with observability and safety frameworks (selfโ€‘hosted orchestration using frameworks such as LangGraph integrated with LLM APIs such as Claude).
  • Strong background in distributed GPU training and inference, cloud infrastructure (AWS/Azure), container orchestration, and ML tooling.
  • Demonstrated ability to lead endโ€‘toโ€‘end AI product development and collaborate with product and design teams to ship userโ€‘facing features.
  • Excellent communication skills, able to present complex architecture and product concepts to executives.
Nice To Have:
  • PhD in Computer Science, Machine Learning, or a related field.
  • Recognized industry presence through publications, patents, talks, or openโ€‘source contributions in LLMs, RAG, or agentic systems.
  • Experience integrating multimodal LLM systems (vision, audio, music, structured data).
  • Leadership in GenAI safety, evaluation, testing, and monitoring.
  • Strong crossโ€‘disciplinary fluency in modeling, infrastructure, product, and design.

The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individualโ€™s knowledge, skills, and experience. Pay ranges may be modified in the future.

Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediggroup.com/life.

Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.

About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.

Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.

Equal Opportunity

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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