MLOps Engineer (JAX, PyTorch, Pallas/Triton)

Key Responsibilities Support research and engineering teams in improving MLOps workflows and model training performance Design technically rigorous tasks and develop high-quality, structured solutions Evaluate ML systems and infrastructure-related outputs, providing clear technical feedback Develop evaluation frameworks and rubrics for training pipelines, distributed systems, and kernel-level optimization Collaborate with subject matter experts to ensure consistency and accuracy across deliverables Core Qualifications Minimum 2 years of professional experience in MLOps, ML infrastructure, or ML systems engineering Hands-on experience with JAX and/or PyTorch in production environments Experience developing or optimizing GPU kernels using Pallas (JAX) or Triton Demonstrated career progression within relevant technical roles Availability to commit at least 30–40 hours per week (weekdays) Strong written communication skills, with the ability to explain complex technical concepts clearly Location Remote (India-based candidates only) Compensation & Employment $35–$45 per hour W-2 employment via Cincinnatus LLC Full-time engagement (40 hours/week) Placement within a leading AI lab’s extended workforce