Zyphra
Zyphra is an artificial intelligence company based in Palo Alto, California
The Role:
As a Machine Learning Engineer , you will be a core contributor to Zyphras Agentic Systems and Interaction projects. You will be at the forefront of building a next-generation desktop and browser-based agent that can autonomously navigate the web, interact with filesystems, and complete complex user tasks. This role spans frontend interfaces, secure sandboxing environments, large-scale document search and retrieval, and language/vision model integration.
Youll work across:
The Role:
As a Machine Learning Engineer , you will be a core contributor to Zyphras Agentic Systems and Interaction projects. You will be at the forefront of building a next-generation desktop and browser-based agent that can autonomously navigate the web, interact with filesystems, and complete complex user tasks. This role spans frontend interfaces, secure sandboxing environments, large-scale document search and retrieval, and language/vision model integration.
Youll work across:
- Design and implementation of an agentic system capable of interacting with browsers, operating systems, and enterprise filesystems
- Building search and retrieval pipelines across large-scale structured and unstructured data
- Integrating LLMs, vision models, reinforcement learning, and scaffolding frameworks for autonomous, multi-step decision-making
- Engineering secure virtualized runtimes and backend services for agent execution
- What matters most is your drive to build production-grade ML systems that push the boundary of what software agents can do
- We value velocity and curiosity, especially in fast-moving and ambiguous environments
- Proficiency in Python and a deep understanding of building and debugging complex ML-driven applications
- Experience working with desktop operating systems (Windows and macOS), including APIs for screen reading, file interaction, and accessibility frameworks
- Experience developing browser extensions or automation tools with fine-grained control over the browser (mouse, tabs, DOM)
- Understanding of LLMs, prompting techniques, and orchestration frameworks for multi-step reasoning
- Ability to work across the full ML stack, from model integration to serving infrastructure
- Experience designing or working with secure and virtualized execution environments
- Excellent communication and collaboration skills across product, research, and engineering teams
- Experience building or integrating retrieval-augmented generation (RAG) systems
- Experience working with enterprise security and compliance frameworks (e.g., SOC 2)
- Familiarity with vector databases and large-scale document indexing
- Knowledge of web automation tools and headless browser environments (e.g, Puppeteer, Playwright)
- Understanding of sandboxed or containerized compute environments with strict access controls
- Comfort designing user-facing agentic workflows and reasoning systems that span multiple modalities (text, vision, actions)
- Experience using and fine-tuning models for screen reading, OCR, or UI understanding
- Background in HCI or interest in building intuitive agent interfaces that extend human capabilities
- Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued
- We strongly value new and crazy ideas and are very willing to bet big on new ideas
- We move as quickly as we can; we aim to minimize the bar to impact as low as possible
- We all enjoy what we do and love discussing AI
- Comprehensive medical, dental, vision, and FSA plans
- Competitive compensation and 401(k)
- Relocation and immigration support on a case-by-case basis
- On-site meals prepared by a dedicated culinary team; Thursday Happy Hours
- In-person team in Palo Alto, CA, with a collaborative, high-energy environment