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How much do shield ai jobs pay per year?

As of Sep 1, 2026, the average yearly pay for shield ai in the United States is $81,277.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $102,000.00 per year, depending on experience, location, and employer.

What is a Shield AI job?

A Shield AI job refers to a role at Shield AI, a company focused on developing artificial intelligence pilots for autonomous aircraft and defense applications. Jobs at Shield AI span various fields, including engineering, data science, product management, and business operations. Employees work on cutting-edge AI and machine learning technologies to enhance national security and defense capabilities. Positions may involve developing software, testing autonomous systems, or supporting military applications. Shield AI seeks professionals with expertise in AI, robotics, aerospace, and related fields.

What types of projects and technologies do employees typically work on at Shield AI?

Employees at Shield AI commonly work on developing and deploying cutting-edge autonomous systems, including unmanned aerial vehicles and AI-driven navigation or perception solutions. Projects often involve cross-functional collaboration with hardware, software, and machine learning teams to solve complex, real-world challenges in defense and security. Team members use advanced technologies such as reinforcement learning, computer vision, and robotics frameworks. This dynamic environment offers the opportunity to work at the forefront of AI innovation while contributing to impactful missions.

What are the key skills and qualifications needed to thrive in the Shield AI position, and why are they important?

To thrive at Shield AI, strong expertise in artificial intelligence, robotics, and software engineering is generally required, often supported by a background in computer science or related technical fields. Familiarity with tools such as Python, ROS (Robot Operating System), simulation platforms, and machine learning frameworks like TensorFlow or PyTorch is typical, along with relevant certifications in cybersecurity or unmanned systems. Excellent problem-solving abilities, strong teamwork, and clear communication are valuable soft skills in this environment. These competencies are crucial for developing reliable autonomous systems that meet real-world standards for safety and performance.

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Shield Ai jobs near you
Infographic showing various Shield Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $81,277 per year, or $39.1 per hour.

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

San Diego, CA

Shield AI
Software Development • 11 - 50 employees
Learn more about Shield AIexternal

Full-time

Re-posted 26 days ago

Job description

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, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. 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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