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Internship Spacex Machine Learning information

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How much do internship spacex machine learning jobs pay per year?

As of Jul 10, 2026, the average yearly pay for internship spacex machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Internship Spacex Machine Learning vs Data Science Intern?

AspectInternship Spacex Machine LearningData Science Intern
Required CredentialsRelevant coursework, basic programming skills, possibly some experience in MLStatistics, programming, data analysis skills, often a related degree
Work EnvironmentHands-on projects in aerospace, collaborative teams, fast-pacedData analysis, modeling tasks, diverse industries, team-based
Employer & Industry UsageSpaceX, aerospace, technology innovationVarious industries including tech, finance, healthcare

Internship Spacex Machine Learning focuses on applying ML techniques to aerospace challenges at SpaceX, emphasizing engineering and technical skills. Data Science Internships are broader, covering data analysis and modeling across multiple industries. Both roles require programming and analytical skills but differ in industry focus and project scope.

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Internship Spacex Machine Learning jobs near you
AI Software Engineer (Vehicle Engineering)

AI Software Engineer (Vehicle Engineering)

SpaceX

Hawthorne, CA • On-site

Full-time

Re-posted 20 days ago

SpaceX rating

8.7

Company rating: 8.7 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

13th of 61 rated aerospace companies

Job description

Job Summary:
SpaceX is a company focused on developing technologies for human exploration of Mars. The AI Software Engineer will be part of the Artificial Intelligence Software Engineering team, solving complex AI data problems for launch vehicles and spacecraft while developing core AI technologies to accelerate engineering processes.
Responsibilities:
• 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
Qualifications:
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
• 1+ years of experience in AI software engineering with a focus on model training, fine-tuning, and machine learning systems
• 1+ years of programming experience in Python
Preferred:
• 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
• Proficiency developing on Linux systems
• Solid understanding of version control (Git), testing, continuous integration, deployment, and monitoring for ML systems
• Experience building complex agentic AI systems and multi-agent workflows
• Experience with data infrastructure for training: relational databases (PostgreSQL), non-relational databases, data lakes, and feature stores (vector databases are a plus)
• Experience deploying containerized applications using Docker and Kubernetes
Company:
SpaceX develops and operates rockets, satellite networks, and AI infrastructure including launch, connectivity, and cloud services. Founded in 2002, the company is headquartered in Hawthorne, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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