> Markdown version of [/jobs/ext/2706953-staff-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2706953-staff-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). --- # Staff Machine Learning Engineer - **Company:** Wand Synthesis AI Inc. - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Nvidia CUDA, Machine Learning, Large Language Models, Build Tools - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/staff-machine-learning-engineer-agent-memory-reasoning-university-wand-synthesis-ai-inc-8828439 ## About the Role * You've shipped production agents or agent adjacent systems at a company, not just in a lab. * Experience with memory, context engineering, or techniques that make agents reason better without retraining them. * An applied, builder's mindset: rigorous thinking, shipped in days and weeks, not semesters. * Comfortable owning ambiguous, senior level problems on your own. * Strong software engineering fundamentals to go with your ML and agent experience. * Practical fluency with the modern agent tooling stack: vector databases (Pinecone, Weaviate, pgvector, or similar), retrieval frameworks (LangChain, LlamaIndex), and agent orchestration tools such as LangGraph. * Comfortable working directly with LLM provider APIs (OpenAI, Anthropic, or similar) and embedding models for retrieval and memory systems. * Experience with agent evaluation and benchmarking tooling (e.g. LangSmith, Ragas, TruLens, or a custom eval harness). * Strong communicator, written and verbal. Preferred Experience * An advanced degree (MS or PhD), paired with real industry experience. * Experience testing and benchmarking agent behavior. * Experience building "skills" or reusable capabilities for AI agents. * Experience with agents that handle serious volumes of complex information (think a genuinely capable assistant, not a demo). * Time spent in a fast scaling product and engineering org. * Experience with large data volumes ## Description We're not fine tuning models. We're teaching agents to reason, remember, and get better without retraining a single one. We're hiring a Staff Machine Learning Engineer to join University, a brand new team we're standing up right now, focused on agent memory, evolution, and reasoning. For at least the next six months: no model training, no fine tuning, no deep GPU or CUDA work. We deploy through the cloud and put our energy into something higher leverage instead. This is one of the more senior technical bars in this hiring round, and one of the most wide open. Role Responsibilities * Build agent memory systems: not just picking what goes into context, but the mechanisms that generate, curate, refine, and store that information in the first place. * Design memory with real constraints: confidentiality and scoping so agents never leak what they shouldn't. * Build systems that watch how agents behave across the org and turn that into shared best practices at scale. * Build reusable "skills" agents can call on: better reasoning, better financial decisions, better report writing. * Design and run tests and benchmarks that show whether these improvements actually work. * Help shape the technical roadmap for agent memory and reasoning as the team stands up. * Take an undefined problem and design a real, shippable solution for it. * Document your methodology clearly enough that others can build on it. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [Building a framework-independent component library](https://www.wearedevelopers.com/videos/1679-building-a-framework-independent-component-library) - [The weekly developer show: Boosting Python with CUDA, CSS Updates & Navigating New Tech Stacks](https://www.wearedevelopers.com/videos/1293-the-weekly-developer-show-boosting-python-with-cuda-css-updates-navigating-new-tech-stacks) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering)