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# AI Engineer

- **Company:** Pytho AI Inc.
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Systems Engineering, Big Data, Continuous Integration, Distributed Computing Environment, Machine Learning, Performance Tuning, Tensorflow, Unstructured Data, Reinforcement Learning, Feature Engineering, Pytorch, Large Language Models, Model Validation, Containerization, Information Technology, Low Latency, HuggingFace, Data Management, Machine Learning Operations, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-engineer-san-francisco-ca--8da9e5af-e9d3-428d-a189-cb27746f50bf

## About the Role

Artificial Intelligence (AI), Problem Solving Skills, Artificial Intelligence (AI), Simulation, Reinforcement Learning, Production Control, Systems Engineering, Data Management, Performance Tuning/Optimization, Unstructured Data, * Bachelor's degree (B.Sc.) in Computer Science

 * Strong software engineering fundamentals
 * Solid understanding of machine learning principles (model evaluation, optimization, bias/variance tradeoffs)
 * Hands-on experience with ML frameworks (PyTorch, TensorFlow, Hugging Face)
 * Experience working with real-world datasets - cleaning, feature engineering, experimentation, and performance analysis
 * Strong communication and collaboration skills
 * Willingness to travel up to 15% to engage with DoW partners
 * Must be eligible to obtain and maintain a U.S. security clearance

Preferred

 * Master's degree (M.Sc.) in Computer Science, Machine Learning, or related field
 * Experience with edge-deployable or offline ML systems
 * Experience optimizing models for latency and compute constraints
 * Familiarity with distributed training or large-scale data processing
 * Exposure to geospatial, multimodal, or reasoning systems
 * Experience with containerization and orchestration tools

## Description

You will work across the full ML lifecycle - transforming messy, real-world data into production-grade models deployed in high-stakes environments. You'll ship fast, work directly with the founders, and have outsized influence on the technical direction of the company., AI/ML Development: Design, train, fine-tune, and deploy ML models to solve real-world operational problems. Own the lifecycle from data exploration and feature engineering to evaluation and production monitoring.

Data & Systems Engineering: Build scalable data pipelines for structured and unstructured data (text, imagery, geospatial, sensor data). Develop reliable training and inference systems optimized for performance and edge deployment.

Engineering Excellence: Integrate models into robust, scalable production systems with strong testing, observability, and CI/CD practices.

Research & Experimentation: Prototype and benchmark new modeling approaches (LLMs, multimodal systems) to improve performance, robustness, and mission impact.