Machine Learning Engineer/Scientist I - Early Career 2025 University Grad

Application close date:

Applications will be accepted on an ongoing basis until the requisition is closed.

At Blue Origin, we envision millions of people living and working in space for the benefit of Earth. We’re working to develop reusable, safe, and low-cost space vehicles and systems within a culture of safety, collaboration, and inclusion. Join our team of problem solvers as we add new chapters to the history of spaceflight!  

This role is part of Blue Origin corporate functions, providing centralized support across Blue Origin business unit teams, functions, and locations.

We are collaborators, doers, and problem-solvers who are relentlessly committed to a culture of safety. This position will directly impact the history of space exploration and will require your commitment and detailed attention towards safe and repeatable space flight. Join us in lowering the cost of access to space and enabling Blue Origin’s vision of millions of people living and working in space to benefit Earth. 

Join us to develop innovative AI models for our Rocket Factory with a collaborative team. We are looking for someone with deep technical expertise that is interested in positively impacting safe human spaceflight. If you are a passionate and high agency individual (have energy to independently drive initiatives, fix problems and improve status quo), we would love to hear from you.

Primary locations:  

We prioritize placing early career engineers in locations where they can be co-located with their team and the relevant hardware they support. The primary locations for this role are listed below. Please indicate in the application where you would be willing to be located.  

• Kent, WA

What you can expect: 

• Specialized early career development opportunities and mentorship during your first year. 
• Meaningful work! You’ll be contributing directly to top company goals. 

Responsibilities include but are not limited to:

• Based upon your desired career path, projects may include the core AI team within the Enterprise Technology group, you will be instrumental in improving the manufacturing processes of space crafts. By helping build novel AI systems that harnesses multimodal information from disparate sources and automatically transforming them, your work will assist manufacturing engineers in our factories, and make them more efficient, reduce latency, and increase velocity of launches. Specific duties are subject to our business unit objectives. Some examples include:
• Design experiments, hypotheses and rigorously benchmark solutions
  • Conduct literature review to identify relevant datasets, models and tools to prototype and improve AI systems in production
  • Develop techniques for data preprocessing, extraction, and synthetic generation
  • Deploy algorithms by creating docker images, spinning up containers, creating endpoints and microservices
  • Document your findings and present to stakeholders

Basic Qualifications:

• Able to start working full-time by the end of 2025.

• BS in Computer Science or relevant (earned within the last year or by Fall 2025).
• Machine Learning
  • Bachelors or Masters with relevant course work - Linear algebra, Statistics, NLP, and Computer Vision
  • 2+ years of experience coding - Python and AI frameworks (TensorFlow/ PyTorch)
  • Background in Deep Learning - vision-language models (VLMs), transformers, training LoRA adapters, model distillation, and fine-tuning
  • Strong mathematical foundations - linear algebra, calculus, statistics
  • Ability to curate large-scale multimodal datasets - data preprocessing and generation of a variety of datasets (synthetic and human-labeled)
  • Experience with ML libraries and tools – pandas, torchvision, NLTK, spaCy, diffusers, vllm, transformers, DSPy, Ray, LangGraph, DeepSpeed etc.)
  • Designing machine learning experiments – understanding and improving model behaviors and proposing solutions for generalization/interpretability
  • Familiarity with reinforcement learning principles.
  • Understanding of AI ethics and responsible AI development practices
• Distributed Systems
  • Expertise with GPU optimization and Cloud platforms (AWS, Azure)
  • Experience with container orchestration tools (Docker, Kubernetes)
  • CI/CD pipeline implementation and management
  • Systems architecture design for AI applications
• Ability to earn trust, maintain positive and professional relationships, and contribute to a culture of inclusion
• Ability to work independently and as part of a team on rapid development programs.
• Relevant internship/co-op and academic pr