At MAI (pronounced âmyâ), 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.
While traditional software has a clear playbook, building the infrastructure for autonomous, intelligent agents is a new frontierâand 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.
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 worldâexecuting 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 agentsâ intelligence.
A Masterâs or PhDâs 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 clean, scalable, and maintainable code.
You are a product-minded engineer who cares deeply about the end-user and is excited to bridge the gap between complex backend systems and a delightful user experience.
You are a systems-level thinker, capable of navigating ambiguity and designing for scalability, reliability, and extensibility.
Experience with ML frameworks (e.g., PyTorch, TensorFlow) or MLOps infrastructure (e.g., MLflow, Kubernetes, serving systems).
Hands-on experience developing with Large Language Models, agentic frameworks (like LangGraph), or building RAG systems.
Bonus points for experience in any of the following:
Data Engineering: Building ETL / streaming pipelines, working with technologies like Spark, Airflow, dbt, or building on a lakehouse architecture.
Unparalleled Learning: You'll be at the forefront of AI engineering, solving novel challenges in building scalable, reliable systems for autonomous agents and LLMs.
High Impact: As an early member of a lean and powerful team, your work will directly shape our core platform, our culture, and the success of our customers.
A Culture of Curiosity: We're a tight-knit team of passionate builders who value transparency, first-principles thinking, and a relentless drive to solve hard problems together.
True Ownership: We believe in empowering our team. You'll have significant autonomy over your work and a clear path for growth as the company scales.
We're offering a stake in our success and a commitment to your well-being. Our total compensation package is designed to support you, both professionally and personally:
Salary: Depending on your years of experience, a base salary range of $160,000 to $225,000.
Equity: We want you to feel invested in our mission, which is why we offer meaningful equity.
Health and Wellness: Our medical, dental and vision coverage is designed to take care of you and your family.
401(k): We'll help you build for your future with a competitive 401(k) program.
Are you ready to build the future with us? We believe in a holistic approach to hiring. If you're passionate about our mission and have a drive to learn and grow, we encourage you to apply even if you don't meet every single requirement. We value potential, curiosity, and hunger. We can't wait to hear from you.
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