> Markdown version of [/jobs/ext/4614829-lead-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/4614829-lead-machine-learning-engineer). 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). --- # Lead Machine Learning Engineer - **Company:** MIXPEEK LLC - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Machine Learning, Open Source Technology, Software Deployment, Retrieval-Augmented Generation, Large Language Models, Deep Learning, Model Validation, Agentic-AI, Machine Learning Operations, Legacy Systems - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25197_863adf4d9e800ab317a99ce5aabdfb9e ## About the Role * 8+ years of experience in ML/AI engineering, including time as a technical lead or manager * Proven track record of leading ML initiatives end-to-end, from problem definition * production deployment * Deep experience with LLMs and/or agentic systems, ideally in real-world, customer-facing applications * Strong understanding of ML fundamentals (deep learning, transformers, model evaluation, tradeoffs) * Experience scaling ML systems in production, including monitoring, iteration, and reliability * Demonstrated ability to lead engineers, influence architecture decisions, and drive technical direction * Comfortable operating in early-stage, ambiguous environments with high ownership * Strong communication skills with the ability to translate complex ML concepts into clear decisions, * Have experience building agentic systems, orchestration layers, or long-context reasoning systems * Are comfortable across the stack (data * modeling * infra * APIs) * Have worked with both open-source and closed LLMs, including fine-tuning or retrieval systems (RAG) * Have a strong product mindset and care deeply about real-world impact, not just model performance ## Description Our goal is to tackle the type of automation problems that require long-context reasoning, tool orchestration across legacy systems, and strict compliance loops: the ones without known answers. We've shipped real agents that handle real customer workflows in production. With a growing customer base and live deployments, we're scaling up fast and looking for deeply technical builders who want to have outsized impact early. Our core engineering team is looking for a hands-on ML Engineering Lead who thrives in early-stage, ambiguous environments. You've led ML systems from v1 to scale, and enjoy defining both the technical direction and the systems that power them. Your mission is to * Own and lead the ML/AI function end-to-end, setting technical direction and standards across the company * Architect and guide the development of multi-modal, agentic AI systems powering real-world workflows * Define and oversee evaluation frameworks, datasets, and performance metrics to continuously improve agent quality * Drive productionization of ML systems, ensuring reliability, scalability, and compliance in real-world environments * Build and mentor a high-performing ML team over time, setting best practices across modeling, experimentation, and deployment