MLOps Tech Lead/Architect with AWS SageMaker

Net2Source (N2S)

Dallas (TX)

Hybrid

USD 130,000 - 160,000

Full time

14 days+

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Job summary

A leading staffing solutions company is seeking an experienced MLOps Tech Lead/Architect in Dallas. This hybrid role focuses on automating ML pipelines, managing AWS infrastructure, and collaborating with data scientists to operationalize models. Candidates should have extensive experience with MLOps, particularly in AWS, Python, and containerization tools.

Qualifications

12+ years of experience with 4+ years in MLOps or related DevOps roles.
Proficient with AWS services like SageMaker, S3, ECS, EKS.
Hands-on experience with MLOps frameworks and orchestration tools.

Responsibilities

Build and automate ML pipelines, ensuring CI/CD.
Collaborate with data scientists for model deployment.
Design and manage AWS cloud infrastructure.

Skills

MLOps expertise

Hands-on AWS MLOps experience

Strong Python coding

Automation with Terraform and GitHub Actions

Containerization with Docker

Tools

AWS SageMaker

Terraform

GitHub Actions

Docker

Job description

Overview

MLOps Tech Lead/Architect with AWS SageMaker

Location: Dallas, TX (Hybrid, 3 days in the office per week) • Duration: 6-12 months

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 with data scientists to containerize, optimize, and deploy models to production with a focus on reproducibility, scalability, and performance.
Infrastructure management: design and manage the AWS cloud infrastructure powering the MLOps platform, using IaC tools to ensure consistency and cost optimization.
Monitoring & observability: implement monitoring, alerting, and logging to track model performance, data integrity, and pipeline health in real time, addressing issues like drift.
Governance & security: enforce best practices for model and data versioning, auditability, security, and access control across the ML lifecycle.
Tooling & frameworks: develop and maintain reusable tools and frameworks to accelerate ML development and empower data science teams.

Required Qualifications

Overall 12+ years of experience with 4+ years in MLOps, ML engineering, or a related DevOps role focusing on ML workflows.
Hands-on AWS MLOps experience, proficient with SageMaker, S3, ECS, EKS, Lambda, SQS, SNS, and IAM.
Strong Python coding skills; automation experience with Terraform and GitHub Actions.
Solid understanding of MLOps/DevOps principles; hands-on with frameworks like SageMaker Pipelines, Model Registry, Weights & Bias, MLflow or Kubeflow, and orchestration tools like Airflow or Argo.
Containerization expertise with Docker; deploying with ECS/EKS.
Experience with model testing, validation, and performance monitoring; familiarity with PyTorch or TensorFlow.
Excellent communication and documentation skills; ability to collaborate with cross-functional teams.

Why Net2Source

Net2Source (N2S) is an award-winning staffing solutions company with a global footprint. We provide career coaching and talent solutions to address the current talent gap.

Equal Employment Opportunity Statement

Net2Source is an Equal Opportunity Employer. We do not discriminate based on age, disability, ethnicity, gender, gender identity or expression, religion, sexual orientation, or any other protected status. All employment decisions are made in compliance with federal, state, and local law.

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