MLOps Engineer - Fully Remote | Upto $110/hr

Obsidian; New York (NY); Remote; USD 100,000 - 130,000; Full time

Job summary

Obsidian is seeking a talented MLOps Engineer to join their cutting-edge GenAI team in New York. This full-time role involves training and evaluating AI models, developing solutions to MLOps problems, and ensuring the accuracy of training data.

Candidates should have over 2 years of experience in ML infrastructure or MLOps, hands-on experience with JAX, and a strong ability to communicate complex technical concepts. Commitment to a 40-hour work week is required.

Qualifications

• 2+ years of experience in ML infrastructure, MLOps, or ML systems engineering.
• Hands-on experience with JAX at scale.
• Experience with custom GPU kernel optimization.

Responsibilities

• Guide teams to improve AI model performance in MLOps.
• Design domain-relevant tasks and write accurate solutions.
• Evaluate MLOps tasks and provide technical feedback.
• Develop evaluation frameworks for training pipeline design.
• Collaborate with experts for accuracy in training data.

Skills

JAX

Kernel-level programming

MLOps

GPU kernels (Pallas/Triton)

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 JAX and kernel-level programming (Pallas/Triton). 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 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 JAX at scale.
• Experience writing or optimizing custom GPU kernels using Pallas or Triton.
• 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.