SpaceX The AI Software Engineer develops core AI technologies to accelerate engineering at SpaceX, including training models on internal data and building agentic AI tools. The role supports engineering tasks across launch vehicles and spacecraft.
Responsibilities
Aerospace experience is not required to be successful here - rather we look for smart, motivated, collaborative engineers who love solving problems and want to make an impact on an inspiring mission. You will have full ownership of challenging problems and work with a team of enthusiastic engineers to design and produce AI solutions that enable SpaceX to move towards our goals at a rapid pace.
Design and train highly reliable, scalable AI/ML models that empower engineers across all SpaceX departments
Design agentic AI systems and multi-agent workflows to perform engineering tasks
Build and optimize large-scale machine learning training pipelines to create next-generation AI applications that transform day-to-day engineering operations
Develop and fine-tune foundation models (LLMs, vision models, multimodal systems) for high-impact SpaceX use cases
Create production-grade AI tools for data analysis, anomaly detection, predictive modeling, and automated decision-making
Collaborate with peers on AI architecture, model design, training strategies, and code reviews
Rapidly build and iterate on AI prototypes, rigorously quantifying model performance, accuracy, and technical constraints
Own the complete AI model lifecycle — from data preparation and training infrastructure to deployment, monitoring, and continuous improvement
Deep-dive into complex engineering problems to identify and implement efficient, custom-trained AI solutions
Establish rigorous AI standards for model validation, safety, reliability, bias mitigation, and data security
Ensure all AI systems undergo thorough testing and validation to deliver accurate, trustworthy, and production-ready outputs
Qualification
Bachelor’s degree in computer scienceStrong foundation in statistics
Required
Bachelor’s degree in computer science, data science, engineering, math, or physics; OR 4+ years of professional experience building and training AI/ML systems in lieu of a degree
5+ years of experience in AI software engineering with a focus on model training, fine-tuning, and machine learning systems (professional and personal projects are applicable)
5+ years of programming experience in Python
Preferred
Strong hands-on experience in AI software engineering with a focus on model training, fine-tuning, and machine learning systems
Expert understanding of LLM transformer architectures and training procedure including pre-training, supervised fine tuning, and reinforcement learning.
Demonstrated experience training and fine-tuning large language models (LLMs) and other foundation models at scale
Proven track record training and optimizing machine learning models for computer vision (object detection, segmentation, 3D reconstruction, etc.)
Deep expertise with modern ML frameworks: PyTorch, TensorFlow, JAX, or equivalent
Experience designing and running large-scale ML training pipelines, including distributed training on GPU clusters, hyperparameter optimization, and experiment tracking
Strong understanding of MLOps best practices: model versioning, experiment management (MLflow, Weights & Biases, etc.), CI/CD for ML, and automated retraining
Strong foundation in statistics, machine learning theory, deep learning architectures, optimization algorithms, and model evaluation
