Staff Software Engineer, Developer Infrastructure
Dropbox
GoJavaPython
Senior AI Research Scientist
Slingshot Aerospace
full-time
Posted on:
Origin: • 🇺🇸 United States • Arizona, California, Colorado, District of Columbia, Florida, Hawaii, Illinois, Kansas, Montana
Visit company websiteJob Level
Senior
Tech Stack
JavaMicroservicesPython
About the role
- Research and design AI systems, models, and advanced machine learning algorithms to augment physics-driven modeling and simulation systems
- 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
- Contribute content to technical invention disclosures, including 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
- 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) Experience with fine-tuning LLMs, prompt engineering, retrieval-augmented generation (RAG), and domain adaptation for scientific/engineering datasets
- (Preferred) Familiarity with Reinforcement Learning (RL) and multi-agent reinforcement learning
- (Preferred) Strong understanding of neural networks, transformer architectures, attention mechanisms, and optimization methods
- (Preferred) Experience building reusable internal tools (connectors, simulation frameworks, evaluation harnesses)
- (Preferred) Peer-reviewed publications and/or presentations in a scientific discipline, AI/ML focus preferred
- (Preferred) Demonstrable combined experience utilizing APIs, microservices, and workflows that merge physics simulation engines with AI training pipelines
- (Preferred) Familiarity with common agentic protocols (MCP, A2A, etc.)
- (Preferred) Practical working experience with physics simulations, Monte Carlo methods, probabilistic modeling, and Bayesian methods
- (Preferred) 6+ years industry or commensurate academic research experience (e.g. PhD and/or MS)
- (Preferred) Knowledge of parallelization, GPU acceleration, and performance optimization for simulations and training workloads
- (Preferred) Experience with space and astrodynamics is valuable but not required
- (Preferred) Demonstrated experience leading the development, implementation, and transition of technology to production is desirable
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