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# Lead Machine Learning Engineer

- **Company:** Saris Corporation
- **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, Large Language Models, Multi-Agent Systems, Deep Learning, Model Validation, Machine Learning Operations, Legacy Systems
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=70a62d4ee53ca347

## 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


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