U
AI Engineer
United States Digital Space LLC
3 hours ago
Full-time
On-site
San Francisco, California, United States
A growing early-stage startup are looking for an AI Engineer. The startup uses AI to Draft and Develop war plans for their Aerospace/Defense partners. They're on a mission to ensure warfighters are prepared for every challenge they face. They build AI-native software for mission-critical workflows — empowering warfighters with adaptive, intelligent technology designed for the pace and complexity of modern conflict. This is an opportunity to join at the earliest stage and build systems that matter. This role is ideal for someone who thrives in a hands-on environment, enjoys solving complex data problems, and wants to push the state-of-the-art in applied AI for defense. You will work across the full ML lifecycle — transforming messy, real-world data into production-grade models deployed in high-stakes environments.
Key Responsibilities
AI/ML Development: Design, train, fine-tune, and deploy state-of-the-art 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, RAG) to improve performance, robustness, and mission impact. Requirements
Bachelor’s degree (B.Sc.) in Computer Science or related field. 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-wo
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AI/ML Development: Design, train, fine-tune, and deploy state-of-the-art 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, RAG) to improve performance, robustness, and mission impact. Requirements
Bachelor’s degree (B.Sc.) in Computer Science or related field. 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-wo
#J-18808-Ljbffr