Senior ML Engineer - Remote, Scale Production Models

Jobs Ai; Los Angeles (CA); Remote; USD 150,000 - 250,000; Full time

Benefits offered by this job

Fully remote

Flexible hours

Annual learning stipend

Health benefits

Job summary

Jobs Ai is seeking a Senior Machine Learning Engineer to design, train, and deploy ML systems in production. You will own models from research through scaled inference, mentoring junior engineers and shaping ML practice across teams.

The role is fully remote with flexible hours, offering a competitive compensation package, learning stipend, and health benefits. Experience with cloud ML infra and modern ML frameworks is essential for impact at scale.

Qualifications

• 5 years in machine learning engineering with production ownership.
• Strong Python skills and deep experience with PyTorch or TensorFlow.
• Experience training and serving models at scale (deep learning, LLMs, or classical ML).
• Hands-on with cloud ML infrastructure (AWS Sagemaker, GCP Vertex, Databricks, or similar).
• Strong software engineering fundamentals (testing, code review, system design).
• Track record of shipping ML systems that delivered measurable business value.

Responsibilities

• Design, train, and deploy machine learning models at production scale
• Lead architecture decisions for training, evaluation, and inference pipelines
• Build evaluation frameworks and monitoring for model quality and drift
• Partner with data engineering on training data pipelines and feature stores
• Mentor junior ML engineers and contribute to ML practice
• Stay current on research and bring proven techniques into production

Skills

Python

PyTorch

TensorFlow

Production ML

Cloud ML Infra

Software Engineering

Model Monitoring

Tools

AWS Sagemaker

GCP Vertex

Databricks

Job description

Jobs Ai is seeking a Senior Machine Learning Engineer to design, train, and deploy ML systems in production. You will own models from research through scaled inference, mentoring junior engineers and shaping ML practice across teams.

The role is fully remote with flexible hours, offering a competitive compensation package, learning stipend, and health benefits. Experience with cloud ML infra and modern ML frameworks is essential for impact at scale.