Zyphra
Machine Learning Engineer - Intelligent Agents & Systems
Zyphra, Palo Alto, California, United States, 94301
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 Zyphra's 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. You'll 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
Requirements:
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
Bonus Qualifications:
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
Why Work at Zyphra:
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
Benefits and Perks:
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
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 Zyphra's 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. You'll 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
Requirements:
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
Bonus Qualifications:
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
Why Work at Zyphra:
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
Benefits and Perks:
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