What are the responsibilities and job description for the Machine Learning Ops Engineer | Remote | $90 –$140/hr position at Call For Referral?
About The Role
This role focuses on advancing next-generation AI systems through large-scale ML infrastructure, training optimization, and framework-level engineering. The work involves supporting cutting-edge GenAI initiatives, improving model performance, and contributing to highly scalable AI training environments.
Position: MLOps Engineer
Type: W2 | Full-Time Contingent Role
Engagement: Remnote Global | Full-time
Compensation: $90–$140/hour
Location: United States (Remote)
Role Responsibilities
- Support AI research and engineering teams in improving ML infrastructure and training systems
- Design advanced MLOps and ML systems tasks with accurate, structured technical solutions
- Evaluate ML systems outputs and provide detailed technical feedback
- Develop evaluation rubrics and frameworks for distributed systems, training pipelines, and kernel-level optimization
- Collaborate with domain experts to maintain consistency and quality across AI training workflows
- Contribute to improvements in large-scale model training performance and infrastructure reliability
Requirements
- 2 years of professional experience in ML infrastructure, MLOps, or ML systems engineering
- Hands-on production experience with JAX and/or PyTorch at scale
- Experience writing or optimizing GPU kernels using Pallas or Triton
- Strong understanding of ML training systems and distributed infrastructure
- Demonstrated career progression in engineering or AI infrastructure roles
- Ability to commit to a full-time 40-hour/week weekday schedule
- Strong written communication and technical documentation skills
Engagement Details
- W2 employment engagement
- Full-time, 40 hours/week
- No conflicting full-time engagements permitted
- Remote role within the United States
- Opportunity to contribute to leading frontier AI initiatives
Application & Onboarding Process
- Upload resume
- AI interview: A short, 15-minute conversational session to assess background and technical expertise
- Follow-up communication with next steps and onboarding details
Salary : $90 - $140