

ML Ops Lead Engineer-Hybrid
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML Ops Lead Engineer (Hybrid) in Dallas, TX, with a contract duration of 3+ months and a pay rate of "Unknown." Key skills required include ML model deployment, CI/CD pipelines, Docker, Kubernetes, and data governance.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
August 13, 2025
π - Project duration
3 to 6 months
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Dallas, TX
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π§ - Skills detailed
#ML Ops (Machine Learning Operations) #Data Engineering #Monitoring #Docker #Scala #Data Ingestion #Cloud #Compliance #Security #Data Science #Model Deployment #Data Governance #DevOps #ML (Machine Learning) #Deployment #Automation #Kubernetes
Role description
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Please Contact: To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Bhupendra Chopade at email address Bhupendra.Chopade@generistek.com can be reached on # 630-576-1937.
We have Contract role ML Ops Lead Engineer-Hybrid for our client at Dallas TX. Please let me know if you or any of your friends would be interested in this position.
Position Details:
ML Ops Lead Engineer-Hybrid-Dallas TX
Location : Dallas, TX 75254 β (Hybrid - office 3days/wk)
Project Duration : 3+ Months Contract
May require travel to plants (Travelling cost will be covered by the client)
Job Summary
We are seeking an ML Ops Engineer to bridge the gap between data science and production systems, ensuring that machine learning models are deployed, monitored, and maintained at scale. You will work closely with data scientists, data engineers, and software developers to design and implement automated, reliable, and secure ML pipelines from development to production.
Key Responsibilities
β’ Model Deployment & Serving
β’ Deploy ML models into production environments using tools such as Docker, Kubernetes, and model serving frameworks (e.g., Tensor Flow Serving, Torch Serve, ML flow).
β’ Implement CI/CD pipelines for ML workflows.
β’ Pipeline Development & Automation
β’ Build and maintain end-to-end machine learning pipelines for data ingestion, preprocessing, training, validation, deployment, and monitoring.
β’ Automate model retraining and versioning to ensure continuous improvement.
β’ Monitoring & Maintenance
β’ Set up monitoring and alerting systems for model performance, data drift, and infrastructure health.
β’ Troubleshoot and resolve model degradation issues in production.
β’ Collaboration & Integration
β’ Collaborate with data scientists to transition models from experimentation to production-ready systems.
β’ Work with DevOps and cloud teams to ensure ML workloads are scalable and cost-efficient.
β’ Security & Compliance
β’ Ensure compliance with data governance, security, and privacy regulations.
β’ Manage role-based access control (RBAC) for ML infrastructure.
To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Bhupendra Chopade at email address Bhupendra.Chopade@generistek.com can be reached on # 630-576-1937.