AI Research Scientist, Applied AI

Posted Yesterday
Be an Early Applicant
Hiring Remotely in United States
Remote or Hybrid
120K-170K Annually
Junior
Aerospace
The Role
Conduct AI and machine learning research integrating advanced algorithms with physics-driven modeling and simulation systems. Develop reinforcement learning, multi-agent, generative, computer vision, and hybrid modeling solutions; build prototypes and AI workflows; collaborate across research, engineering, and product teams; support technical publications, presentations, invention disclosures, and patent development.
Summary Generated by Built In
Meet Slingshot

At Slingshot Aerospace, we're on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We're a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software.

We move fast, we're not afraid to fail, and we believe the best ideas can come from anywhere—whether you're in engineering, sales, product, or operations. If you want to work on something that truly matters, with people who care deeply about the impact we're making and help shape the future of an industry that's just getting started, you're in the right place.

Meet Slingshot 

At Slingshot Aerospace, we’re on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We’re a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software. 

What You’ll Be Launching 

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. 

Your Mission (Should you choose to accept it) 

  • 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 

Pre-flight Checklist 

  • Must have an Active US Security Clearance (Secret Minimum, Top Secret Preferred) US Security Clearances

  • 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 

 

Bonus Cargo 

  • 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 

 

We're building a constellation here, not looking for identical satellites. Every member of the team brings different capabilities to the same mission. If your orbit intersects with ours and you're mission-ready, send it. 

 

Location: Remote, US  

Salary Range: $120,000 - $170,000 + Equity and Benefits 

Classification: Full-time Exempt (computer professional exemption) 

US-based Candidates: we are currently only able to hire residents of the following U.S. states: AL, AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MA, MD, MI, MN, MO, MT, NC, NJ, NM, NV, NY, OH, OK, OR, RI, TN, TX, UT, VA, WA, WI, WV 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.

Skills Required

  • Active United States security clearance at Secret level or higher; Top Secret preferred
  • Master’s degree in a related field with at least two years of similar experience, or a PhD with relevant research projects
  • Demonstrable AI and machine learning expertise, including applicable AI/ML methodologies
  • Familiarity with object-oriented 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 maintenance processes, including GitHub, code reviews, or CI/CD
  • Ability to work in multidisciplinary teams across military, government, and industry partners
  • Excellent verbal and written communication skills
  • Experience fine-tuning LLMs, prompt engineering, retrieval-augmented generation, or domain adaptation for scientific and engineering datasets
  • Familiarity with reinforcement learning and multi-agent reinforcement learning
  • Understanding of neural networks, transformer architectures, attention mechanisms, and optimization methods
  • Experience building reusable internal tools, simulation frameworks, connectors, or evaluation harnesses for AI agent training
  • Hands-on experience developing and deploying supervised or unsupervised learning models
  • Peer-reviewed articles, conference papers, or presentations in a science or engineering discipline
  • Experience using APIs, microservices, and workflows combining physics simulation engines with AI training pipelines
  • Familiarity with agentic protocols such as MCP or A2A
  • Experience with physics-based simulation and statistical methods such as Monte Carlo, probabilistic, or Bayesian methods
  • Working knowledge of parallel computing, GPU acceleration, and performance optimization
  • Experience with space and astrodynamics

Slingshot Aerospace Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Slingshot Aerospace and has not been reviewed or approved by Slingshot Aerospace.

  • Fair & Transparent Compensation Base salaries for core engineering, specialized technical roles, and sales are considered fair to above average, with salary ranges publicly posted for open roles. Feedback suggests this transparency helps set clear expectations and reinforces confidence in offer fairness.
  • Healthcare Strength Medical, dental, and vision coverage are described as robust, with some plans company-paid. Feedback suggests the healthcare package is a standout contributor to overall satisfaction.
  • Leave & Time Off Breadth Flexible or unlimited PTO, paid sick days and holidays, and parental leave support work-life integration in a remote-first environment. Feedback suggests employees value the ability to take time off, even if usage can depend on team norms.

Slingshot Aerospace Insights

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The Company
HQ: El Segundo, CA
150 Employees
Year Founded: 2017

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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