Net2Source (N2S)
Overview
Position: MLOps Tech Lead/ Jr. Architect Location: Dallas, TX (Hybrid, 3 days per week in office) Type: Contract Compensation
Base pay range: $60.00/hr - $65.00/hr Company
Join a Global Leader in Workforce Solutions Net2Source Inc. Responsibilities
Build & Automate ML Pipelines: Design, implement, and maintain CI/CD pipelines for machine learning models, ensuring automated data ingestion, model training, testing, versioning, and deployment. Operationalize Models: Collaborate closely with data scientists to containerize, optimize, and deploy their models to production, focusing on reproducibility, scalability, and performance. Infrastructure Management: Design and manage the underlying cloud infrastructure (AWS) that powers our MLOps platform, leveraging Infrastructure-as-Code (IaC) tools to ensure consistency and cost optimization. Monitoring & Observability: Implement comprehensive monitoring, alerting, and logging solutions to track model performance, data integrity, and pipeline health in real-time. Proactively address issues like model or data drift. Governance & Security: Establish and enforce best practices for model and data versioning, auditability, security, and access control across the entire machine learning lifecycle. Tooling & Frameworks: Develop and maintain reusable tools and frameworks to accelerate the ML development process and empower data science teams. Required Qualifications
Experience: Overall 10+ years of experience with 4+ years of experience in MLOps, Machine Learning Engineering, or a related DevOps role with a focus on ML workflows. Cloud Expertise: Extensive hands-on experience in designing and implementing MLOps solutions on AWS. Proficient with core services like SageMaker, S3, ECS, EKS, Lambda, SQS, SNS, and IAM. Coding & Automation: Strong coding proficiency in Python. Extensive experience with automation tools, including Terraform for IaC and GitHub Actions. MLOps & DevOps: A solid understanding of MLOps and DevOps principles. Hands-on experience with MLOps frameworks like Sagemaker Pipelines, Model Registry, Weights and Bias, MLflow or Kubeflow and orchestration tools like Airflow or Argo Workflows. Containerization: Expertise in developing and deploying containerized applications using Docker and orchestrating them with ECS and EKS. Model Lifecycle: Experience with model testing, validation, and performance monitoring. Good understanding of ML frameworks like PyTorch or TensorFlow is required to effectively collaborate with data scientists. Communication: Excellent communication and documentation skills, with a proven ability to collaborate with cross-functional teams (data scientists, data engineers, and architects). Why Work With Us?
We believe in more than just jobs—we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter. Our Commitment to Inclusion & Equity Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics. Awards & Recognition
America's Most Honored Businesses (Top 10%) Fastest-Growing Staffing Firm by Staffing Industry Analysts INC 5000 List for Eight Consecutive Years Top 100 by Dallas Business Journal Spirit of Alliance Award by Agile1 Ready to Level Up Your Career?
Click
Apply Now
and let's make it happen. Seniority level
Mid-Senior level Employment type
Contract Job function
Engineering and Information Technology Industries
Staffing and Recruiting
#J-18808-Ljbffr
Position: MLOps Tech Lead/ Jr. Architect Location: Dallas, TX (Hybrid, 3 days per week in office) Type: Contract Compensation
Base pay range: $60.00/hr - $65.00/hr Company
Join a Global Leader in Workforce Solutions Net2Source Inc. Responsibilities
Build & Automate ML Pipelines: Design, implement, and maintain CI/CD pipelines for machine learning models, ensuring automated data ingestion, model training, testing, versioning, and deployment. Operationalize Models: Collaborate closely with data scientists to containerize, optimize, and deploy their models to production, focusing on reproducibility, scalability, and performance. Infrastructure Management: Design and manage the underlying cloud infrastructure (AWS) that powers our MLOps platform, leveraging Infrastructure-as-Code (IaC) tools to ensure consistency and cost optimization. Monitoring & Observability: Implement comprehensive monitoring, alerting, and logging solutions to track model performance, data integrity, and pipeline health in real-time. Proactively address issues like model or data drift. Governance & Security: Establish and enforce best practices for model and data versioning, auditability, security, and access control across the entire machine learning lifecycle. Tooling & Frameworks: Develop and maintain reusable tools and frameworks to accelerate the ML development process and empower data science teams. Required Qualifications
Experience: Overall 10+ years of experience with 4+ years of experience in MLOps, Machine Learning Engineering, or a related DevOps role with a focus on ML workflows. Cloud Expertise: Extensive hands-on experience in designing and implementing MLOps solutions on AWS. Proficient with core services like SageMaker, S3, ECS, EKS, Lambda, SQS, SNS, and IAM. Coding & Automation: Strong coding proficiency in Python. Extensive experience with automation tools, including Terraform for IaC and GitHub Actions. MLOps & DevOps: A solid understanding of MLOps and DevOps principles. Hands-on experience with MLOps frameworks like Sagemaker Pipelines, Model Registry, Weights and Bias, MLflow or Kubeflow and orchestration tools like Airflow or Argo Workflows. Containerization: Expertise in developing and deploying containerized applications using Docker and orchestrating them with ECS and EKS. Model Lifecycle: Experience with model testing, validation, and performance monitoring. Good understanding of ML frameworks like PyTorch or TensorFlow is required to effectively collaborate with data scientists. Communication: Excellent communication and documentation skills, with a proven ability to collaborate with cross-functional teams (data scientists, data engineers, and architects). Why Work With Us?
We believe in more than just jobs—we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter. Our Commitment to Inclusion & Equity Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics. Awards & Recognition
America's Most Honored Businesses (Top 10%) Fastest-Growing Staffing Firm by Staffing Industry Analysts INC 5000 List for Eight Consecutive Years Top 100 by Dallas Business Journal Spirit of Alliance Award by Agile1 Ready to Level Up Your Career?
Click
Apply Now
and let's make it happen. Seniority level
Mid-Senior level Employment type
Contract Job function
Engineering and Information Technology Industries
Staffing and Recruiting
#J-18808-Ljbffr