AI Research Scientist, Applied AI

Slingshot Aerospace

2h•$120,000 - $170,000•Remote

About The Position

As an AI Research Scientist, you will join the AI and Innovation department within Slingshot’s Technology organization. You will contribute directly to Slingshot’s vision to accelerate space sustainability and create a safer, more connected world. You will participate in the identification, development, and integration of novel algorithms and models, leveraging diverse data streams and advanced intelligence engines, and the subsequent integration of those technologies into prototypes and broader AI systems across the Slingshot platform.

Requirements

Must have an Active US Security Clearance (Secret Minimum, Top Secret Preferred)
Masters in related field + Minimum of 2 years' experience in similar role (or PhD with relevant research projects)
AI/ML expertise
Demonstrable experience in the application of AI/ML methodologies including, but not limited to, deep learning, generative models (e.g. LLMs, diffusion models), agentic systems, reinforcement learning, computer vision, or other emerging areas of AI research
Software development experience
Familiarity with object-oriented paradigms and functional programming principles
Expertise in at least one modern high-level programming language (e.g. Python, R, C++, Java)
Collaborative source code management and maintenance processes (e.g. Github, code reviews, CI/CD)
Ability to work within multi-disciplinary teams in a fast-paced, evolving operational environment that spans military, government, and industry partners
Excellent verbal and written communication skills
Passion for Space and AI/ML applications

Nice To Haves

Experience with fine-tuning LLMs, prompt engineering, retrieval-augmented generation (RAG), and domain adaptation for scientific/engineering datasets using modern ML frameworks and model hubs
Familiarity with Reinforcement Learning (RL) and multi-agent reinforcement learning to enable training agents that learn strategies in simulation and real-world contexts
Practical understanding of neural networks, transformer architectures, attention mechanisms, and optimization methods to extend or fine-tune transformer-based models
Experience building reusable internal tools (connectors, simulation frameworks, evaluation harnesses) to refine simulation-based datasets for AI agent training in support of research, data-driven insights/analytics, and model development
Hands-on experience supporting the development and deployment of supervised and/or unsupervised learning models
One or more peer reviewed articles, conference papers, and/or presentations in a science or engineering discipline
Demonstrable combined experience indicative of skillsets required to utilize APIs, microservices, and workflows that merge physics simulation engines with AI training pipelines
Familiarity with common agentic protocols (MCP, A2A, etc...)
Practical working experience with physics-based simulation, and statistical methods (e.g. monte Carlo methods, probabilistic modeling, and Bayesian methods)
Working knowledge of parallel computing, GPU acceleration, and performance optimization for simulations and training workloads.
Experience with space and astrodynamics is valuable but not required

Responsibilities

Engage in relevant research and development (R&D) of AI systems, models, and advanced machine learning algorithms that augment physics-driven modeling and simulation systems
Explore and implement AI-powered simulation tooling in support of AI workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches
Collaborate with research, engineering, and product teams to build AI-powered solutions that meet mission-critical modeling and decision-support needs
Engage in and support the drafting and review of conference and journal articles and presentations, sharing advances with both internal stakeholders and the wider research community.
Contribute content to technical invention disclosures, including associated narrative, graphics, and engagements in support of patent development
Perform additional responsibilities (no more than 10% of duties) in support of the company’s technology and product development initiatives