Mondo Staffing
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MLOps Engineer, Location is Remote. The start date is August 25, 2025, or ASAP for this 3.5-month contract role with potential extension. \n Job Title:
MLOps Engineer Location-Type:
Remote Start Date Is:
August 25, 2025, or ASAP Duration:
3.5 months (Contract, potential extension) Compensation Range:
$55.00/hr - $65.00/hr W2 \n Job Description: We are seeking an
MLOps Engineer
to design, implement, and manage infrastructure for deploying and maintaining machine learning models in production. This role sits at the intersection of
Data Science, Data Engineering, and DevOps , requiring expertise in
cloud platforms, automation, and ML lifecycle management . \n Day-to-Day Responsibilities: \n
\n
Design and deploy
scalable ML infrastructure
using cloud and containerization (Azure, AKS, Kubernetes, Docker).
\n
Build
CI/CD pipelines
for model deployment, monitoring, and retraining.
\n
Collaborate with Data Scientists and Engineers to implement
model validation and testing procedures .
\n
Optimize and refactor ML development code for production readiness.
\n
Develop
data and feature engineering pipelines
to support models.
\n
Configure and automate environment builds in production.
\n
Ensure
scalability, reliability, and continuous enhancement
of ML systems.
\n
\n Requirements: \n Must-Haves: \n
\n
Strong experience with
Kubernetes, AKS, and Azure Cloud .
\n
Hands-on expertise with
Azure DevOps and Databricks .
\n
Proven experience in
building and managing ML infrastructure .
\n
Familiarity with
CI/CD for ML model deployment .
\n
Ability to collaborate with cross-functional teams in a fast-paced environment.
\n
\n Nice-to-Haves: \n
\n
MLOps or ML infrastructure deployment experience.
\n
Exposure to advanced ML lifecycle automation frameworks.
\n
Knowledge of
monitoring and retraining pipelines
for AI/ML models. \n
MLOps Engineer, Location is Remote. The start date is August 25, 2025, or ASAP for this 3.5-month contract role with potential extension. \n Job Title:
MLOps Engineer Location-Type:
Remote Start Date Is:
August 25, 2025, or ASAP Duration:
3.5 months (Contract, potential extension) Compensation Range:
$55.00/hr - $65.00/hr W2 \n Job Description: We are seeking an
MLOps Engineer
to design, implement, and manage infrastructure for deploying and maintaining machine learning models in production. This role sits at the intersection of
Data Science, Data Engineering, and DevOps , requiring expertise in
cloud platforms, automation, and ML lifecycle management . \n Day-to-Day Responsibilities: \n
\n
Design and deploy
scalable ML infrastructure
using cloud and containerization (Azure, AKS, Kubernetes, Docker).
\n
Build
CI/CD pipelines
for model deployment, monitoring, and retraining.
\n
Collaborate with Data Scientists and Engineers to implement
model validation and testing procedures .
\n
Optimize and refactor ML development code for production readiness.
\n
Develop
data and feature engineering pipelines
to support models.
\n
Configure and automate environment builds in production.
\n
Ensure
scalability, reliability, and continuous enhancement
of ML systems.
\n
\n Requirements: \n Must-Haves: \n
\n
Strong experience with
Kubernetes, AKS, and Azure Cloud .
\n
Hands-on expertise with
Azure DevOps and Databricks .
\n
Proven experience in
building and managing ML infrastructure .
\n
Familiarity with
CI/CD for ML model deployment .
\n
Ability to collaborate with cross-functional teams in a fast-paced environment.
\n
\n Nice-to-Haves: \n
\n
MLOps or ML infrastructure deployment experience.
\n
Exposure to advanced ML lifecycle automation frameworks.
\n
Knowledge of
monitoring and retraining pipelines
for AI/ML models. \n