MLOps Engineer

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Applied AI Engineering

MLOps Engineer

MLOps Engineers manage the end-to-end lifecycle of machine learning models.

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Overview

MLOps Engineers manage the end-to-end lifecycle of machine learning models.

Responsibilities

• Design MLOps pipelines: Implement automated pipelines for model training, testing, deployment, and monitoring.
• Collaborate with data scientists: Optimize deployment and integration of models into production systems.
• Automate testing and quality control: Build tests for model performance and monitor drift.
• Ensure version control and reproducibility: Manage artifacts, track experiments, and implement rollback strategies.
• Optimize pipelines: Improve performance, reliability, and compliance with security standards.
  
  

Qualifications

• Bachelor's or master's degree in computer science or related field.
• Experience with CI/CD, version control systems, and container orchestration.
• Strong programming skills in Python and ML frameworks.
  
  

Equal opportunity

TAIRC evaluates candidates using role-related evidence and documented review criteria. Employment decisions must not be based on protected personal characteristics.

Engagement pathways and compensation status

TAIRC is currently building its funding base. Opportunities identified as volunteer or unpaid do not provide compensation at this stage. Any future paid appointment would require available funding, organizational approval, applicable legal compliance, and a separate written agreement. Participation does not guarantee future employment or compensation.

• Volunteer contribution interest may be reviewed only as a voluntary, scoped pathway.
• Educational internship interest requires separate supervision, educational purpose, and legal review.
• Advisory expressions of interest are not board or formal advisory appointments.
• Future compensated employment is contingent on funding, approval, legal compliance, and a separate written offer.
  
  

Accessibility and accommodations

For an accommodation or alternate submission format, contact [email protected]. The application form does not request medical documentation or sensitive identity documents.

Posting information

Department Applied AI Engineering

Public role ID TAIRC-ROLE-018

Status Open

Location, employment type, workplace type, compensation, sponsorship policy, posted date, and closing date are omitted unless HR has entered approved factual values.

Recruitment privacy

Application data is used for recruitment review, stored with restricted access, and handled under the recruitment privacy and retention policy.