

MLOps/LLMOps Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps/LLMOps Engineer on a remote, contract basis at $100/hour. Key skills include Kubernetes, Docker, CI/CD, and MLflow. Requirements involve cloud services knowledge, Python/Bash proficiency, and experience with LLM-specific frameworks.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
800
-
ποΈ - Date discovered
August 5, 2025
π - Project duration
Unknown
-
ποΈ - Location type
Remote
-
π - Contract type
Unknown
-
π - Security clearance
Unknown
-
π - Location detailed
United States
-
π§ - Skills detailed
#Security #Automated Testing #Observability #Batch #Load Balancing #Terraform #Containers #Data Quality #Deployment #Kubernetes #Ansible #Docker #MLflow #GCP (Google Cloud Platform) #AWS (Amazon Web Services) #Cloud #Monitoring #Logging #Data Pipeline #Bash #"ETL (Extract #Transform #Load)" #Azure #Python #Automation
Role description
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Position: MLOps/LLMOps Engineer
Location: Remote
Pay: $100/hour
Experience: Expertise in Kubernetes, Docker, CI/CD tools, and MLflow or similar platforms.
Type: Contract
Schedule: Monday - Friday
Conde Group is seeking an MLOps/LLMOps Engineer to join a growing and dynamic team!
Job Description:
β’ Ensure GenAI solutions move from prototype to production with proper operational support.
β’ Establish specialized monitoring for model performance, inference latency, and data quality.
β’ Create high-performance deployment architectures that balance speed, cost, and reliability.
β’ Enable efficient scaling of LLM solutions across multiple business units.
β’ Develop operational data pipelines to continuously improve model performance with new utility-specific data.
β’ Configure GPU infrastructure on-premises or in the cloud with appropriate CI/CD pipelines for model updates.
β’ Design and implement LLM-specific deployment architectures with Docker containers for both batch and real-time inference.
β’ Build comprehensive monitoring and observability systems with appropriate logging, metrics, and alerts.
β’ Implement load balancing and scaling solutions for LLM inference, including model sharding if necessary.
β’ Create automated workflows for model retraining, versioning, and deployment.
β’ Optimize infrastructure costs through intelligent resource allocation, spot instances, and efficient compute strategies.
β’ Collaborate with PG&E's Cyber team on implementing appropriate security controls for GenAI applications.
β’ Develop automated testing frameworks to ensure consistent output quality across model updates.
Position Requirements:
β’ Cloud & Infrastructure: Understanding of GPU instance options, cloud services (AWS/Azure/GCP), and optimization techniques
β’ Automation: Proficiency in Python, Bash, and infrastructure-as-code tools like Terraform or Ansible
β’ LLM-Specific Frameworks: Experience with tools like TensorBoard, MLFlow, or equivalent for scaling LLMs
β’ Performance Optimization: Knowledge of techniques to monitor and improve inference speed, throughput, and cost
β’ Collaboration: Ability to work effectively across technical teams while adhering to enterprise architecture standards
Job Perks:
β’ Medical Insurance
β’ 401K
Conde Group does not just connect you with a job; we offer a Professional Mentoring & Education Program to help you be great at your job, love it, and grow.
Conde Group is part of Array Corporation, the leading technology-enabled workforce solutions company whose mission is to fix how labor is bought, sold and delivered to enable universal access to the American Dream.
We are proud to be an Equal Employment Opportunity and Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.