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Foundation Models Jobs in Washington (NOW HIRING)

Cynet Systems

Senior Data Scientist

Washington, DC · On-site

Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications. * Fine-tune or adapt open-source and proprietary models. * Build high-performance ...

New

Cisco

Applied AI Scientist

Arlington, VA

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

New

Cisco

Applied AI Scientist

Mclean, VA

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

New

Cisco

Applied AI Scientist

Ashburn, VA

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

New

Cisco

Applied AI Scientist

Washington, DC

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

New

Cisco

Applied AI Scientist

Rockville, MD

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

New

Kapitus

MLOps Architect - Gen Al

Arlington, VA

Data ingestion & preprocessing o Feature engineering / embedding generation o Model training & fine-tuning (traditional ML + foundation models) * Model evaluation & validation * Deployment (real-time ...

Kapitus

MLOps Architect

Arlington, VA · On-site

$117K - $189K/yr

Data ingestion & preprocessing o Feature engineering / embedding generation o Model training & fine-tuning (traditional ML + foundation models) * Model evaluation & validation * Deployment (real-time ...

CYNET SYSTEMS

Senior Data Scientist

Washington, DC · On-site

$65/hr

Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications. * Fine-tune or adapt open-source and proprietary models. * Build high-performance ...

New

Vantor

Applied AI Scientist

Herndon, VA · On-site

... in foundation models, generative AI, multimodal learning, and reasoning systems, and translate research breakthroughs into practical systems. • Maintain high engineering standards through code ...

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Foundation Models information

How do foundation models make money?

Foundation models make money primarily by providing AI services and solutions to businesses, such as customizing models for specific applications or licensing access to pre-trained models. Companies may also generate revenue through cloud-based deployment, consulting, and ongoing support, leveraging skills in machine learning and data management.

What does a foundation model do?

A foundation model is a large-scale machine learning model trained on diverse data that can be adapted for various tasks such as natural language processing or computer vision. It serves as a base for developing specialized applications by fine-tuning or prompting. Data scientists and AI engineers often work with these models using tools like TensorFlow or PyTorch.

What is the highest paying model job?

Senior roles in foundation model development, such as Lead AI Researcher or Machine Learning Director, tend to be the highest paying jobs in the field, often offering six-figure salaries or higher. These positions require advanced expertise in deep learning, large-scale model training, and experience with high-performance computing environments.

What are the most popular foundation models?

In the context of foundation models for AI jobs, the most popular include OpenAI's GPT series, Google's BERT and T5, Meta's LLaMA, and Facebook's RoBERTa. These models are widely used for natural language processing tasks and often require expertise in deep learning frameworks like TensorFlow or PyTorch.
What are popular job titles related to Foundation Models jobs in Washington? For Foundation Models jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Foundation Models jobs in Washington look for? The top searched job categories for Foundation Models jobs in Washington are:
What cities in Washington are hiring for Foundation Models jobs? Cities in Washington with the most Foundation Models job openings:
Foundation Models jobs near you
Product Manager, AI/ML & Foundation Models (R4991)

Product Manager, AI/ML & Foundation Models (R4991)

Shield AI

Washington, DC

Full-time

Re-posted 10 days ago

Job description

Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
 
The Product Manager will drive the strategy and execution of Shield AI's next-generation autonomy intelligence stack-enabling customers and internal teams to train, evaluate, and deploy foundation and domain models that power resilient autonomy at the edge. This PM owns the product vision and roadmap for the Hivemind AI Platform (Forge, training pipelines, data infrastructure, evaluation, and deployment toolchains), ensuring we can manufacture, govern, and field advanced world models, robotics foundation models, and vision-language-action systems safely and at scale. 
 
This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning-capabilities that are central to Shield AI's strategic direction. 
 
This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.
What you'll do:
  • AI Model Development & Training Platform
  • Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines.
  • Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization.
  • Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.
  • Data, Simulation & Synthetic Data Factory
  • Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation.
  • Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.
  • Safe Deployment & Model Governance
  • Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence.
  • Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments.
  • Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.
  • Edge Deployment & AI Factory Integration
  • Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors.
  • Define requirements for distillation, quantization, and inference tooling as part of the "three-computer" development and deployment model.
  • Ensure closed-loop workflows between cloud model training and edge-native execution.
  • Cross-Functional Leadership
  • Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints.
  • Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories.
  • Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.
  • User & Customer Impact
  • Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform.
  • Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements.
  • Lead demos and onboarding for model-development capabilities across internal and external teams.
Required qualifications:
  • 7+ years of experience in product management or highly technical ML/AI product roles.
  • 2+ years of experience in a hands-on software development role.
  • Strong engineering background (Computer Science, Electrical Engineering, Robotics, or related field).
  • Deep understanding of foundation models, robotics models, multimodal models, MLOps, and training infrastructure.
  • Experience managing complex products spanning data pipelines, cloud training clusters, model governance, and edge deployments.
  • Proven success partnering with research teams to transition ML innovations into stable, production-grade workflows.
  • Familiarity with simulation-based data generation and large-scale data management.
  • Excellent communicator with strong cross-functional leadership skills.
Preferred qualifications:
  • Experience working on autonomy, robotics, embedded AI, or mission-critical systems.
  • Hands-on familiarity with GPU infrastructure, distributed training, or data lakehouse architectures.
  • Experience supporting defense, dual-use, or safety-critical AI systems.
  • Background designing or operating AI Factory-style pipelines (data training evaluation distillation edge deployment).
  • Advanced degree in engineering, ML/AI, robotics, or a related field.
$190,000 - $290,000 a year
#LI-DM2
#LE

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
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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