ML Engineer: Self-Learning Agents (On-site SF)

Wajo AI; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Wajo AI in San Francisco, CA is seeking a Machine Learning Engineer to design, implement, and deploy self-learning models and agents for real-world applications. You will work on-site with researchers and engineers to translate ideas into production systems, build data pipelines, run experiments, and monitor deployed services for reliability and safety.

You will collaborate across teams to optimize performance, document findings, and contribute to roadmap planning in a fast-paced research-driven

Qualifications

• Strong ML and DL fundamentals including RL, supervised and unsupervised learning.

Responsibilities

• Design, implement, and deploy self-learning models and agents for real-world applications.
• Develop and optimize ML algorithms and data pipelines.
• Run experiments, evaluate model performance, and iterate on architectures.
• Integrate models into scalable services and APIs.
• Monitor production systems and improve reliability, safety, and efficiency.
• Document work, participate in code reviews, and contribute to roadmap discussions.

Skills

Reinforcement learning

Supervised learning

Unsupervised learning

Python

PyTorch

TensorFlow

Data pipelines

Experimentation

Docker

Cloud platforms

Production deployment

Debugging

Cross-functional teamwork

Education

Bachelor's in CS

Advanced degree

Equivalent experience

Tools

Docker

Kubernetes

AWS

GCP

Job description

Wajo AI in San Francisco, CA is seeking a Machine Learning Engineer to design, implement, and deploy self-learning models and agents for real-world applications. You will work on-site with researchers and engineers to translate ideas into production systems, build data pipelines, run experiments, and monitor deployed services for reliability and safety.

You will collaborate across teams to optimize performance, document findings, and contribute to roadmap planning in a fast-paced research-driven