ML Systems Engineer - Fully Remote | Upto $110/hr

Role Overview

ML Systems Engineer (Fully Remote)

You will guide research and engineering teams to improve AI model performance by covering knowledge gaps across MLOps, training infrastructure, and ML systems/framework-level topics. The role is a 40 hours/week contract.

Responsibilities

• Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level areas.
• Design challenging, domain-relevant tasks and produce accurate, well-structured solutions for MLOps and ML systems problems.
• Evaluate MLOps tasks/solutions and provide clear, written technical feedback.
• Create guidelines, rubrics, and evaluation frameworks for assessing:
  • training pipeline design
  • distributed systems reasoning
  • kernel-level optimization
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Requirements (Must-Have)

• 2+ years of professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized top-tier organization.
• Hands-on production experience with PyTorch at scale.
• Experience writing/optimizing custom GPU kernels using Triton or Pallas.
• Demonstrable career progression.
• Ability to reliably work at least 40 hours/week on weekdays.
• Strong written communication skills; ability to clearly explain complex technical decisions.

Contract / Compensation

• Type: Contract (W-2 employment via Cincinnatus LLC)
• Rate: $70–$110/hour

Application Process

• Submit resume and complete an AI interview based on your resume (20–30 minutes).