Source description
About the role
COMPANY OVERVIEW
Prepare first. Decide first. Win first.
At Pytho, we're on a mission to ensure warfighters are prepared for every challenge they face. We are committed to assembling a world-class team of exceptional problem solvers, combining expert engineering talent with deep experience in National Security.
We build AI for the most important problem in defense — making sure the force is ready to fight. Our software is deployed and in use with DoW partners today.
THE OPPORTUNITY
We're building out our AI Engineering Team. This is a chance to join at the earliest stage of a company where the engineering problems are genuinely hard — planning under uncertainty, multi-agent coordination, simulation, reinforcement learning — and the work is deployed in environments where the output actually matters.
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.
KEY RESPONSIBILITIES
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.
WHAT YOU BRING
Required
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Bachelor's degree (B.Sc.) in Computer Science
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Strong software engineering fundamentals
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Solid understanding of machine learning principles (model evaluation, optimization, bias/variance tradeoffs)
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Hands-on experience with ML frameworks (PyTorch, TensorFlow, Hugging Face)
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Experience working with real-world datasets — cleaning, feature engineering, experimentation, and performance analysis
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Strong communication and collaboration skills
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Willingness to travel up to 15% to engage with DoW partners
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Must be eligible to obtain and maintain a U.S. security clearance
Preferred
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Master's degree (M.Sc.) in Computer Science, Machine Learning, or related field
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Experience with edge-deployable or offline ML systems
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Experience optimizing models for latency and compute constraints
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Familiarity with distributed training or large-scale data processing
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Exposure to geospatial, multimodal, or reasoning systems
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Experience with containerization and orchestration tools
Benefits
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Competitive salary and equity
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Opportunity to help build a category-defining defense tech company
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Full health benefits
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401(k)
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Offices in Washington DC and San Francisco
