Machine Learning Engineer

Machine Learning Engineer Location: Mountain View, CA Company Stage of Funding: Seed Stage AI Startup ($25M Raised) Office Type: Onsite (Hybrid Available for San Francisco-Based Employees) Salary: $160,000–$225,000 + Competitive Equity Company Description We're representing a rapidly growing AI startup building autonomous agents for the $1 trillion digital advertising industry. Their platform enables businesses to automate performance marketing through AI agents that continuously optimize campaigns, make intelligent spending decisions, and improve customer acquisition outcomes. Backed by Kleiner Perkins in one of the largest seed financings of the year, the company has quickly grown to more than 25 employees while serving dozens of customers with a rapidly expanding waitlist. Founded by leaders with deep experience building advertising and e-commerce platforms at scale, the team is combining machine learning, agentic AI, and modern data infrastructure to redefine how businesses approach growth and marketing automation. What You Will Do Design and build the core machine learning systems that power autonomous AI agents for performance marketing. Develop production-ready machine learning models that optimize advertising spend, click-through rates, conversions, and customer acquisition. Build agentic AI systems capable of reasoning, planning, and making intelligent decisions across complex marketing workflows. Architect scalable data platforms using modern lakehouse architectures, streaming pipelines, and ML serving infrastructure. Develop robust ETL pipelines and feature engineering workflows that support model training and inference. Build customer-facing AI applications that enable users to collaborate with intelligent agents. Partner closely with data scientists to productionize state-of-the-art machine learning and reasoning models. Improve model performance through experimentation, evaluation, monitoring, and continuous iteration. Collaborate across engineering, product, and research teams to translate customer needs into scalable AI solutions. Help shape the technical direction of a rapidly growing AI platform from the ground up. Ideal Background 3–8 years of professional experience as a Machine Learning Engineer. Strong experience building and deploying production machine learning models with measurable business impact. Expertise developing production-quality Python applications. Experience with modern ML frameworks such as PyTorch or TensorFlow. Experience building end-to-end machine learning systems rather than exclusively ML infrastructure. Strong understanding of recommendation systems, advertising technology, search, ranking, or relevance modeling. Experience building LLM-powered applications, agent frameworks, or retrieval-augmented generation (RAG) systems. Familiarity with modern data engineering tools such as Spark, Airflow, dbt, or lakehouse architectures. Bachelor's degree in Computer Science (with professional software engineering experience) or a Master's/PhD in Computer Science or a related technical field. Preferred Experience at leading technology companies or high-growth startups focused on advertising, search, recommendations, or AI. Background at companies such as Google, Meta, Pinterest, Reddit, Uber, Spotify, Netflix, Instacart, TikTok, DoorDash, or similar organizations. Experience building agentic AI systems using frameworks such as LangGraph or similar orchestration platforms. Experience with Kubernetes, MLflow, model serving infrastructure, and production MLOps workflows. Strong product intuition with experience building AI systems that directly influence customer-facing metrics. Startup experience combined with large-scale production engineering experience. Excellent communication skills and ability to thrive in highly collaborative, fast-moving environments. Passion for AI innovation, experimentation, and building products from the ground up. Compensation and Benefits Base salary: $160,000–$225,000. Competitive early-stage equity package. H-1B transfer sponsorship available. Hybrid flexibility for employees commuting from San Francisco. Opportunity to join one of the best-funded AI seed startups in the market. Work directly with an experienced team of engineers and operators from leading AI, advertising, and technology companies. Significant ownership over core machine learning systems that directly drive customer outcomes. Fast interview process with the ability to complete the process in approximately two weeks. Opportunity to help define the future of autonomous AI agents within the rapidly growing performance marketing industry. Recruiting from Scratch