Jaxon is looking to make AI trustworthy for mission-critical environments, particularly for the U.S. Space Force, by advancing machine learning capabilities to meet the rigor and reliability required for national security operations.
Requirements
- Python
- Python Data Science Stack - NumPy, Pandas, Scikit Learn, various deep learning and NLP libraries
- Langraph, LlamaIndex and/or other agentic libraries
- Docker, Docker Compose, K8s and related container orchestration technologies
- Hands-on experience running local LLMs using technologies such as Ollama and Transformers
- Familiarity with knowledge representation
- Familiarity with so-called “hybrid databases” like Apache AGE
Responsibilities
- Collaborate Across Teams: Work with cross-functional, geographically distributed teams to integrate ML models into our existing systems and workflows, enhancing product capabilities.
- Optimize Data Processing and Model Performance: Conduct comprehensive data management including preprocessing, feature engineering, and model evaluation to improve accuracy and efficiency.
- Technical Proficiency with an NLP focus: Demonstrate solid machine learning engineering experience, particularly with NLP applications and unstructured data in a cloud environment.
- Understand Large Language Models: Operationalize intimate familiarity with the model deployment process, optimization of LLM parameters for specific behaviors, and a general understanding of LLM functionality and use cases.
- Build and train and/or fine-tune models, not just calling cloud APIs
- Digesting academic papers and understanding that it's code that matters
- Have an understanding of both the fundamentals and applications of different NLP approaches
Other
- Existing SECRET security clearance strongly preferred; eligibility to obtain clearance is required if not already held
- Ability to context switch as needed
- Ability to communicate findings and recommendations clearly and constructively to peers, management, partners, and customers
- Ability to effectively explain highly technical details to less technically focused decision makers
- Bachelor's degree in Computer Science or similar, MS or PhD in Computer Science, Statistics, Physics, Mathematics or any related Engineering field preferred
