PyTorch MLOps Engineer - AI Specialist

Mercor; New York (NY); On-site; USD 120,000 - 140,000; Full time

Job summary

Obsidian is seeking talented MLOps Engineers to join their cutting-edge GenAI team. This role focuses on building foundational AI models and involves AI model training, evaluation, and generating high-quality training data.

Candidates should have 2+ years of experience in ML infrastructure or MLOps and hands-on production experience with PyTorch. The position is full-time, requiring 40 hours of engagement per week with no other commitments.

Qualifications

• 2+ years of professional experience in ML infrastructure, MLOps, or ML systems engineering.
• Hands-on production experience with PyTorch at scale.
• Experience writing or optimizing custom GPU kernels using Triton or Pallas.

Responsibilities

• Guide research and engineering teams to improve AI model performance.
• Design tasks and write solutions to MLOps and ML systems problems.
• Evaluate MLOps tasks and provide technical feedback.

Skills

MLOps expertise

PyTorch

Kernel-level programming

Written communication

Job description

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

Overview

Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented MLOps Engineers with deep, hands-on expertise in PyTorch and kernel-level programming (Triton/Pallas). This role involves AI model training and evaluation work, including writing and assessing MLOps tasks and solutions to generate high-quality training data for frontier AI systems.

This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce. This is a 40-hour full-time engagement, with no conflicts/no other engagements.

Key Responsibilities

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

Core Qualifications

• 2+ years of dedicated 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 or optimizing custom GPU kernels using Triton or Pallas.
• Demonstrable career progression.
• Ability to engage reliably for at least 40 hours/week during weekdays.
• Strong written communication skills and the ability to explain complex technical decisions clearly.

Equal Employment Opportunity

Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.