AI Research Scientist

This opportunity is for an Artificial Intelligence Researcher focused on applied AI, advanced machine learning, simulation, and research-driven product development. The role involves identifying, developing, testing, and integrating novel algorithms and AI models into prototypes and broader technology systems.

This position supports the development of AI-powered solutions that combine diverse data streams, advanced intelligence engines, physics-driven modeling, simulation workflows, and modern machine learning methods. The work includes hands-on research and development, technical collaboration with engineering and product teams, scientific communication, and support for invention disclosures and patent-related materials.

Employment Type: Full-time

Salary Range: $120,000 - $170,000 per year

What You’ll Do

• Conduct research and development of AI systems, machine learning models, and advanced algorithms that support and enhance physics-driven modeling and simulation systems.
• Explore and implement AI-powered simulation tools that support AI workflows, including reinforcement learning, multi-agent systems, and hybrid modeling approaches.
• Collaborate with research, engineering, and product teams to build AI-powered solutions for mission-critical modeling, analytics, and decision-support needs.
• Support the drafting and review of conference papers, journal articles, and technical presentations for internal stakeholders and the broader research community.
• Contribute technical content for invention disclosures, including written narratives, supporting graphics, and related materials for patent development.
• Help integrate novel algorithms, models, and AI technologies into prototypes and larger AI systems.
• Work with diverse data streams and advanced intelligence engines to support applied AI research and product development.
• Perform additional technology and product development responsibilities as needed, limited to no more than 10% of the role.

Qualifications

• Active U.S. Security Clearance is required, with Secret clearance as the minimum and Top Secret clearance preferred.
• Master’s degree in a related field with at least 2 years of experience in a similar role, or a PhD with relevant research projects.
• Strong expertise in artificial intelligence and machine learning.
• Demonstrated experience applying AI/ML methods such as deep learning, generative models, large language models, diffusion models, agentic systems, reinforcement learning, computer vision, or other emerging areas of AI research.
• Software development experience in research, applied AI, engineering, or technical product environments.
• Familiarity with object-oriented programming paradigms and functional programming principles.
• Expertise in at least one modern high-level programming language, such as Python, R, C++, or Java.
• Experience with collaborative source code management and software maintenance processes, including GitHub, code reviews, and CI/CD workflows.
• Ability to work effectively with multidisciplinary teams in a fast-paced and evolving operational environment.
• Ability to collaborate across teams and stakeholders connected to military, government, and industry environments.
• Excellent verbal and written communication skills.
• Strong interest in space-related applications and AI/ML technologies.

Preferred Qualifications

• Experience fine-tuning large language models, using prompt engineering, building retrieval-augmented generation workflows, and adapting models for scientific or engineering datasets.
• Experience using modern machine learning frameworks and model hubs.
• Familiarity with reinforcement learning and multi-agent reinforcement learning for training agents in simulation and real-world contexts.
• Practical understanding of neural networks, transformer architectures, attention mechanisms, and optimization methods.
• Experience extending or fine-tuning transformer-based models.
• Experience building reusable internal tools, such as connectors, simulation frameworks, and evaluation harnesses.
• Experience refining simulation-based datasets for AI agent training, research, analytics, and model development.
• Hands-on experience supporting the development and deployment of supervised or unsupervised learning models.
• One or more peer-reviewed articles, conference papers, or presentations in a science or engineering discipline.
• Experience using APIs, microservices, and workflows that connect physics simulation engines with AI training pipelines.
• Familiarity with common agentic protocols, including MCP, A2A, or similar protocols.
• Practical experience with physics-based simulation and statistical methods, including Monte Carlo methods, probabilistic modeling, and Bayesian methods.
• Working knowledge of parallel computing, GPU acceleration, and performance optimization for simulation and model training workloads.
• Experience with space systems or astrodynamics is valuable but not required.

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