About the Position
In this role, you will join the AI and Data Science department within Slingshot’s Research and Development (R&D) organization. You will contribute directly to Slingshot’s vision to accelerate space sustainability and create a safer, more connected world. You will identify opportunities for AI to contribute to Slingshot’s mission goals by pioneering novel algorithms that leverage diverse data streams and advanced intelligence engines and by integrating the advancements into broader AI systems across the Slingshot technology platform.
Slingshot Aerospace cares deeply about our commitment to company values, mission, and purpose. The core competencies we will be looking to identify include intellectual agility, ability to develop innovative solutions, leadership, performance orientation, and industry expertise.
What You’ll Do
- Research and design AI systems, models, and advanced machine learning algorithms to augment physics-driven modeling and simulation systems and enable intelligent AI agents to reason, plan, and adapt based on simulated and real-world sensor data
- Lead innovation in AI-driven simulation tooling, identifying opportunities to enhance workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches
- Collaborate with research, engineering, and product teams to build AI-driven solutions that meet mission-critical modeling and decision-support needs
- Publish, and present research outcomes at approved conferences and peer-reviewed journals 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 data science and product development initiatives
Requirements
- AI/ML expertise
- Demonstrable experience in the application of sophisticated AI/ML methodologies to science and/or engineering disciplines, including deep learning, generative models (e.g. LLMs, diffusion models), agentic systems, reinforcement learning, computer vision, or other emerging areas of AI research
- Hands-on experience developing and deploying supervised and/or unsupervised learning models
- Software development experience
- Familiarity with object-oriented or functional programming principles
- Expertise in at least one 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
- Must be a U.S. citizen eligible for government clearances
Preferred Qualifications
- 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
- Strong 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
- Peer-reviewed publications and/or presentations in a scientific discipline, AI/ML focus preferred
- 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 simulations, Monte Carlo methods, probabilistic modeling, and Bayesian methods
- 6+years industry or commensurate academic research experience (e.g. PhD and/or MS) in scientific or AI/ML-related domains
- Knowledge of parallelization, GPU acceleration, and performance optimization for simulations and training workloads.
- Experience with space and astrodynamics is valuable but not required
- Demonstrated experience leading the development, implementation, and transition of technology to production is desirable
These skills are guidelines, not hard and fast rules. You don’t have to meet every qualification listed - if your skills are transferable and you meet the minimum requirements, we encourage you to apply.
Location: Remote, US
Salary: $170,000 - $210,000
Classification: Full-time Exempt (computer professional exemption)
US-based Candidates: we are currently only able to hire residents of the following U.S. states: AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NM, NY, NC, OR, RI, TN, TX, UT, VT, VA, WA, WV, and WI. We are unable to consider candidates residing in other U.S. states at this time.
Internationally-based Candidates: we are currently only able to hire residents of the following locations: United Kingdom. We are unable to consider candidates residing in other countries at this time.
Equity, Diversity & Inclusion are key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, and backgrounds, who share a passion for creating a safer, more connected world. Diversity not only includes race and gender identity, but also national origin, citizenship, sex, color, veteran status, disability, genetic information, or any other protected characteristic that is part of one’s identity. All of our employees’ points of view are key to our success, and we embrace individuality.
Top Skills
What We Do
Slingshot Aerospace builds world-class space simulation and analytics solutions. We are driven by our vision of accelerating space sustainability to create a safer, more connected world.
Space is increasingly complex due to the exponential growth of global launch activity, the proliferation of new data sources, and the ever-growing body of new satellites and debris. Organizations are making mission-critical decisions in this high-risk environment and they need the right information at the right time. Slingshot Aerospace empowers government and commercial space organizations to better design, manage, and safeguard their assets, as well as mitigate risks, to ensure safe and reliable operations for all space-faring users.
We are achieving this by bringing the space domain into the digital environment and fusing together data from different sources to provide a full, dynamic orbital picture. In doing so, Slingshot Aerospace customers can make decisions at the speed of relevance and achieve clarity in complex environments.
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