Real-Time ML Engineer — Low-Latency Production Models

Beltic; United States; Remote; USD 120,000 - 230,000; Full time

Job summary

Beltic is seeking a seasoned machine learning engineer to design, deploy, and monitor real-time models in production. You will build feature pipelines, handle training and evaluation, and ensure low-latency serving for live applications.

You can work remotely from anywhere in the Americas (UTC-8 to UTC-3) or on-site in San Francisco; candidates with strong Python, PyTorch or TensorFlow, SQL, and software engineering discipline will thrive in a fast-moving environment.

Qualifications

• Experience implementing production ML models from data exploration to deployment.
• Strong Python programming and experience with PyTorch or TensorFlow; solid SQL skills.
• End-to-end production ML systems: feature pipelines, training, evaluation, and low-latency serving.
• Comfort with low-label and cold-start problems such as anomaly detection and weak supervision.
• Data analysis, statistics, and principled experiment design.
• Strong software engineering: versioned, testable, reproducible code.

Skills

Production ML

Python

PyTorch or TensorFlow

SQL

Low-latency serving

Experiment design

Software engineering

Anomaly detection

Education

Bachelor's in CS/Math/Related

Tools

Git

Docker

Job description

Beltic is seeking a seasoned machine learning engineer to design, deploy, and monitor real-time models in production. You will build feature pipelines, handle training and evaluation, and ensure low-latency serving for live applications.

You can work remotely from anywhere in the Americas (UTC-8 to UTC-3) or on-site in San Francisco; candidates with strong Python, PyTorch or TensorFlow, SQL, and software engineering discipline will thrive in a fast-moving environment.