Machine Learning Engineer
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.
What You’ll Do
- Build the Agent's Operating System: 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: Architect our foundational data and signal platform using a modern lake house architecture. 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: 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: Build our customer-facing applications, including a seamless chat UI where users collaborate with their AI partners. Own the reliable and scalable serving infrastructure required to deliver a world-class, 24/7 experience.
- Bring Models to Life: 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 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.
Compensation And Benefits
- Salary: Depending on your years of experience, a base salary range of $160,000 to $225,000.
- Equity: Meaningful equity offered.
- Health and Wellness: Medical, dental, and vision coverage.
- 401(k): Competitive 401(k) program.
Why You’ll Love Working at MAI
- 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.
Compensation Range
$160K - $225K