ML Engineer — Real-Time AI Infrastructure

happyrobot.ai; San Francisco (CA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Healthcare, dental, vision

Equity

Job summary

HappyRobot is building AI workers that can make decisions and operate across enterprise systems. We’re seeking a talented ML engineer to design, build, and deploy scalable ML systems, overseeing the full lifecycle from data ingestion to production. Join as an early ML hire to shape technology direction.

You will implement end-to-end ML pipelines, apply robust MLOps practices, and collaborate with product and engineering teams to deliver real-time AI features with high efficiency and reliability.

Qualifications

• Strong experience in machine learning, deep learning and NLP.
• Solid background in MLOps and data pipelines — model deployment, monitoring, and scaling in production.
• Proficiency in Python; familiarity with Go.

Responsibilities

• Design, build, and maintain scalable ML systems from data ingestion to deployment.
• Develop end-to-end ML pipelines (data collection, labeling, training, validation, monitoring).
• Implement robust MLOps practices including model versioning, CI/CD for ML, and production monitoring.
• Collaborate with product and engineering to deploy models into real-time products.

Skills

ML

Deep Learning

NLP

Python

Go

MLOps

Data pipelines

Model deployment

CI/CD

Monitoring

Tools

MLflow

Kubeflow

Weights & Biases

Airflow

Dagster

Job description

HappyRobot is building AI workers that can make decisions and operate across enterprise systems. We’re seeking a talented ML engineer to design, build, and deploy scalable ML systems, overseeing the full lifecycle from data ingestion to production. Join as an early ML hire to shape technology direction.

You will implement end-to-end ML pipelines, apply robust MLOps practices, and collaborate with product and engineering teams to deliver real-time AI features with high efficiency and reliability.