Machine Learning Engineer
Mai
| Company | Mai |
| Category | Engineering |
| Location | Mountain View |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 160k–225k |
| Posted | 28 Jan 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
ABOUT US
At MAI (pronounced “my”), we're on a mission to democratize advanced advertising technology. We believe that cutting-edge marketing tools, once exclusive to large enterprises with massive budgets, should be accessible to everyone. Our platform uses AI agents to automate and optimize performance marketing, empowering small and mid-sized businesses to scale their ad spend profitably without the need for an agency or endless hours of manual campaign management.
Founded by ad platform veterans from Google and Instacart, we've successfully raised a $25 million Seed funding round led by Kleiner Perkins to accelerate our growth. This capital will be used to expand our product and engineering teams, bringing our vision of intelligent, autonomous marketing to life. Our AI agents have already proven their value, helping clients drive 40% more sales and managing millions in monthly Google Ads spend. Our client waitlist is growing by the day.
WHY JOIN NOW
While traditional software has a clear playbook, building the infrastructure for autonomous, intelligent agents is a new frontier—and we're writing the manual.
As an early Machine Learning Engineer at MAI, you won't just be writing code; you'll be the architect of the entire ecosystem where our AI agents live, learn, and operate. You will have a profound impact across our entire stack, from the foundational data platforms that feed our agents, to the core agentic frameworks that allow them to reason, to the scalable serving systems that deliver their intelligence to our customers. This is a rare opportunity to build a truly AI-native product from the ground up and solve problems at the forefront of the industry.
You won't just be a cog in a large machine. You'll be an athlete on a small, focused team of fewer than ten engineers, with immense impact and the ability to shape the future of our company. We're in the early days of forming three core teams:
- Product Engineering & Infrastructure
- AI Platform & Foundation
- Agent Application & Quality
You'll have the unique chance to learn and grow your skillset as these teams evolve. We encourage you to lean on your specializations while taking on new projects you've never done before, learning from your peers and becoming a more well-rounded engineer.
WHAT YOU’LL DO
- Build the Agent's Operating System: You will design and build our core agentic platform. This is the engine that allows us to craft, manage, and continuously improve our autonomous agents by orchestrating complex workflows, enabling long-term memory, and integrating human feedback loops.
- Engineer the Data Engine: You will architect our foundational data and signal platform using a modern lake house architecture. You'll build the robust pipelines and ML serving systems that fuel our agents with the critical, real-time signals they need to make intelligent, high-stakes decisions.
- Create World-Class Tools for AI: An agent is only as good as its tools. You will build a suite of powerful, reliable, and safe "tool machines" that allow our agents to interact with the world—executing code in a secure python sandbox, manipulating data, and calling third-party APIs accurately.
- Ship an Exceptional Product Experience: You will build our customer-facing applications, including a seamless chat UI where users collaborate with their AI partners. You'll also own the reliable and scalable serving infrastructure required to deliver a world-class, 24/7 experience.
- Bring Models to Life: You will collaborate closely with data scientists to build the MLOps infrastructure for training, fine-tuning, and deploying state-of-the-art reasoning models that form the core of our agents’ intelligence.
WHAT YOU'LL BRING
- A Master’s or PhD’s degree in Computer Science or a related quantitative field, OR a Bachelor's degree with 2+ years of professional software engineering experience.
- Strong proficiency in Python and a passion for writing c
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