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# Machine Learning Engineer

- **Company:** Recruiting from Scratch
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $160,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Airflow, Extract Transform Load (ETL), Machine Learning, Automation of Marketing, Recommender Systems, Software Tools, Tensorflow, Software Engineering, Feature Engineering, Pytorch, Large Language Models, Apache Spark, Generative AI, Agentic-AI, Fastapi, Build Management, AI Platforms, Kubernetes, Information Technology, Data Management, Machine Learning Operations, Virtual Agents, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/machine-learning-engineer-san-francisco-ca--34fd7bf2-836d-4c20-b4f9-543ae84ceac8

## About the Role

Machine Learning, Startup, Artificial Intelligence (AI), Seed Funding, Advertising, Artificial Intelligence (AI) Agents, Customer Acquisition, Marketing, Campaigns, Marketing Automation Software, * 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.

## Description

* 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.