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ML Systems Engineer - AI Trainer

  • ML Systems Engineer - AI Trainer job type Posted on: Nov 09, 2026
  • ML Systems Engineer - AI Trainer experience level Mercor
  • ML Systems Engineer - AI Trainer employment type Chicago, Illinois
  • ML Systems Engineer - AI Trainer salary Salary: $120 per hour
  • ML Systems Engineer - AI Trainer employment type Remote
  • ML Systems Engineer - AI Trainer salary Full-time

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Job Title :

ML Systems Engineer - AI Trainer

Job Type :

Full-Time

Job Location :

Chicago Illinois United States

Remote :

Yes

Jobcon Logo Job Description :

Job Description

Job Description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: MLOps Engineer, LLM Systems (Serving, GPU Kernels, Profiling)
Type: Contract
Compensation: $90–$120/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

  • Design challenging tasks across GPU kernels, performance profiling, debugging, and inference serving. Write accurate, well-structured solutions.
  • Guide research and engineering teams to close knowledge gaps and improve AI model performance on ML systems and training infrastructure.
  • Evaluate MLOps and ML systems tasks. Provide clear, written technical feedback that stands up to reviewer scrutiny.
  • Develop guidelines and detailed rubrics covering kernel-level optimization, profiler output interpretation, and serving throughput and latency trade-offs.
  • Collaborate with other subject matter experts to ensure training data consistency and accuracy.

Qualifications

Must-Have

  • 2+ years of hands-on professional experience in ML systems, ML infrastructure, or GPU performance engineering.
  • Practical experience in GPU kernels (e.g., CUDA, Triton) or performance profiling (e.g., Kineto, torch.profiler).
  • Working production experience with JAX and/or PyTorch.
  • Familiarity with modern accelerators such as A100, H100, or TPU.
  • Strong written communication skills.

Compensation & Legal

  • W-2 employment with Cincinnatus LLC.
  • Equal Employment Opportunity employer.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



#hiringmercor

Jobcon Logo Position Details

Posted:

Nov 09, 2026

Reference Number:

366c294a

Employment:

Full-time

Salary:

$120 per hour

City:

Chicago

Job Origin:

ziprecruiter

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Job Description

Job Description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: MLOps Engineer, LLM Systems (Serving, GPU Kernels, Profiling)
Type: Contract
Compensation: $90–$120/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

  • Design challenging tasks across GPU kernels, performance profiling, debugging, and inference serving. Write accurate, well-structured solutions.
  • Guide research and engineering teams to close knowledge gaps and improve AI model performance on ML systems and training infrastructure.
  • Evaluate MLOps and ML systems tasks. Provide clear, written technical feedback that stands up to reviewer scrutiny.
  • Develop guidelines and detailed rubrics covering kernel-level optimization, profiler output interpretation, and serving throughput and latency trade-offs.
  • Collaborate with other subject matter experts to ensure training data consistency and accuracy.

Qualifications

Must-Have

  • 2+ years of hands-on professional experience in ML systems, ML infrastructure, or GPU performance engineering.
  • Practical experience in GPU kernels (e.g., CUDA, Triton) or performance profiling (e.g., Kineto, torch.profiler).
  • Working production experience with JAX and/or PyTorch.
  • Familiarity with modern accelerators such as A100, H100, or TPU.
  • Strong written communication skills.

Compensation & Legal

  • W-2 employment with Cincinnatus LLC.
  • Equal Employment Opportunity employer.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



#hiringmercor

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