# AI Engineer at Pytho Ai > Onsite · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Apytho-ai%3Aae2b666d-f41d-4310-bccf-84462e1bb2bf (read 2026-11-11). ## Facts (observed) - Company: [Pytho Ai](https://alderhq.app/companies/pytho-ai) - Location text: San Francisco - Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco") - Posted: 2026-03-16 (240 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/pytho-ai/ae2b666d-f41d-4310-bccf-84462e1bb2bf - Skills listed (inferred): PyTorch, TensorFlow, LLMs ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (SF Bay Area, n 544): p25 $200k, median $249k, p75 $300k ## Description (the employer's text) ### 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 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 ### Benefits Competitive salary and equity Opportunity to help build a category-defining defense tech company Full health benefits 401(k) Offices in Washington DC and San Francisco --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Apytho-ai%3Aae2b666d-f41d-4310-bccf-84462e1bb2bf and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.