Machine Learning Engineer
2 weeks ago
Position 1
:
MLOps Engineer II (Mid-Level)
Location
: Remote (Night Shift – 10 PM to 7 AM CST)
Contract
: 12 months (Renewable)
Start Date
: December 1, 2025
Role Overview
We are seeking a
proficient MLOps Engineer (Level II)
with 2–4 years of experience in
ML operations, pipelines, and production deployments
. The ideal candidate will be hands-on, detail-oriented, and capable of working independently to ensure ML models are deployed, monitored, and maintained effectively.
Responsibilities
- Deploy and maintain ML models in production (AWS SageMaker, MLflow, Kubeflow).
- Manage CI/CD pipelines and infrastructure as code (Terraform, ArgoCD).
- Support ETL/data workflows using Airflow or Astronomer.
- Collaborate with data scientists to transition models into production environments.
- Troubleshoot issues, perform root cause analysis, and drive remediation.
Qualifications
- 2–4 years of experience in
MLOps or DevOps
. - Strong Python skills for automation & workflow management.
- Hands-on with cloud ML tools and orchestration frameworks.
- Familiarity with CI/CD and monitoring best practices.
Position 2
:
MLOps Engineer III (Senior-Level)
Location
: Remote (Night Shift – 10 PM to 7 AM CST)
Contract
: 12 months (renewable)
Start Date
: December 1, 2025
Role Overview
We are hiring a
Senior MLOps Engineer (Level III)
with 4–6 years of experience designing and scaling
ML infrastructure
. This role requires technical leadership, mentorship, and deep expertise in automation and hybrid environments. The Engineer III will set best practices, lead monitoring strategies, and ensure reliable integration across teams.
Responsibilities
- Lead design of
scalable MLOps frameworks
and automation strategies. - Build and optimize monitoring/alerting systems for
drift, accuracy, and latency
. - Manage governance and versioning with GitHub Enterprise and JFrog Artifactory.
- Enhance deployment/retraining pipelines (Terraform, ArgoCD).
- Partner with Big Data and Work Routing teams for system reliability.
- Mentor junior engineers and lead
knowledge transfer sessions
.
Qualifications
- 4–6 years of experience in
MLOps, DevOps, or ML Engineering
. - Advanced proficiency in automation, pipelines, and
hybrid infra (on-prem + cloud)
. - Hands-on expertise with Terraform, ArgoCD, and orchestration tools.
- Strong leadership and communication skills.
Why Join?
- Be part of an
INSPYR Solutions Managed Service team
. - Work on cutting-edge
production ML infrastructure
. - Fast selection
: one interview with the hiring manager. - Opportunity to contribute to a
long-term, high-impact engagement
.
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