> Markdown version of [/jobs/ext/4669858-principal-machine-learning-engineer-in-palo-alto](https://www.wearedevelopers.com/jobs/ext/4669858-principal-machine-learning-engineer-in-palo-alto). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer in Palo Alto - **Company:** Energy Jobline - **Location:** Palo Alto, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Programming, Distributed Systems, Machine Learning, Tensorflow, Azure Machine Learning, SAP (Applications), Search Technologies, Software Engineering, Systems Architecture, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Agentic-AI, Information Technology, Machine Learning Operations - **Published:** November 11, 2026 - **Apply:** https://www.energyjobline.com/job/principal-machine-learning-engineer-palo-alto-32219037 ## About the Role 10+ years of software engineering experience with a track record of delivering complex systems Bachelor's degree in Computer Science, Mathematics, Physics, or related field Hands-on experience with AI/ML in production environments, including large models (LLM), retrieval-augmented (RAG), prompt engineering, vector search, agent workflows, and model evaluation techniques Expertise in distributed systems design and large-scale enterprise product architecture Strong programming skills, proficiency with ML frameworks, and solid understanding of MLOps practices Excellent English communication skills and ability to collaborate effectively in global, multicultural teams ## Description You will architect ML solutions, lead deployment at scale, and ensure compliance with performance and security standards. You'll act as a trusted advisor and contribute to SAP's AI strategy. What you'll bring You have deep expertise in advanced ML system architecture, scalable model deployment, and ML platform capabilities. You are expected to have a solid understanding of modern AI application development, including large models, retrieval-augmented (RAG), prompt engineering, vector search, agent workflows, and model evaluation techniques. You are the technical partner who can bridge the gap between customer requirements and product capabilities and are comfortable working directly with stakeholders, gathering requirements, clarifying ambiguous requests, and proposing solutions that maximize customer value. Your ability to guide teams, optimize workflows, and connect emerging ML advancements to business needs is what this level is built around. Experience with large-scale ML architecture design, advanced MLOps and observability, model governance and explainability, and optimization across performance and cost dimensions is expected. Technical mentorship and the ability to set standards that others follow are also part of what you'll bring. What you'll build You'll lead the design and optimization of large-scale ML systems (LLM capabilities and infrastructure), shape cutting-edge infrastructure, mentor engineers, and define architectural and operational standards. Ensuring ML solutions meet business, performance, scalability, and governance requirements, while advancing the adoption of modern ML techniques, is a central part of the role. You'll influence technical direction across products, enable safe experimentation, and ensure systems are production-ready and aligned with product objectives. Where you belong You'll shape how ML engineering is practiced across teams and products, not just within your immediate group. The role requires both technical depth and the ability to influence people who don't report to you. Mentoring engineers is an explicit expectation, and the standards you set will affect work well beyond your direct area. If you've reached the point where your value comes as much from what you enable in others as from what you build yourself, this level reflects that. Skills used in this role include: Design & Architecture, Leadership & Impact, Managing ambiguity, Engineering Excellence, Quality Mindset, Context engineering, AI output quality assurance, Agentic AI day-to-day practice, AI-Assisted Automation and Prototyping, AI adoption capability, Learning Agility, Collaboration, Complex problem solving, Creative thinking, Effective communication, For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process. Please note that any violation of these guidelines may result in disqualification from the hiring process.