Data Science & ML Architecture Lead (MLOps, Cloud)

Machine Learning Technologies, LLC; Dallas (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking an experienced Data Science Architect to design, architect, and lead scalable data science, ML, and AI solutions for enterprise applications. You will work with data scientists, engineers, and business stakeholders to establish scalable architecture, standards, and best practices.

The role emphasizes MLOps, model deployment, and cloud platforms (AWS, Azure, GCP) with hands-on work in Python, SQL, Spark, Databricks, and ML frameworks.

Qualifications

• 9+ years of experience in Data Science, ML, AI, or related technology disciplines.
• Strong experience in Data Science Architecture / Machine Learning Architecture / AI Architecture.
• Advanced programming experience with Python.
• Strong knowledge of SQL, data modeling, data structures, and algorithms.
• Strong understanding of machine learning algorithms, statistical modeling, predictive analytics, and data mining.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
• Hands-on experience with MLOps, ML lifecycle management, model deployment, monitoring, and CI/CD.
• Experience designing scalable data pipelines and distributed data processing.
• Strong experience with Apache Spark / PySpark and/or Databricks.
• Experience with one or more cloud platforms: AWS, Azure, or Google Cloud Platform.
• Knowledge of data platforms such as Data Lakes, Data Warehouses, Lakehouse architectures, and distributed databases.
• Experience with REST APIs, microservices, containers, Docker, and Kubernetes is preferred.
• Strong understanding of data governance, security, privacy, and enterprise architecture principles.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.

Responsibilities

• Design and develop end-to-end Data Science, Machine Learning, and AI architectures for enterprise applications.
• Define scalable and secure architectures for data ingestion, processing, analytics, machine learning, and model deployment.
• Lead the architecture and implementation of predictive analytics, machine learning, statistical modeling, and advanced analytics solutions.
• Collaborate with Data Scientists and Data Engineers to develop robust data pipelines and analytical platforms.
• Design solutions for both structured and unstructured data and large-scale data processing.
• Develop and implement machine learning models using appropriate algorithms and frameworks.
• Establish standards and best practices for model development, validation, deployment, monitoring, and lifecycle management.
• Design and implement MLOps processes and CI/CD pipelines for machine learning workloads.
• Architect cloud-based data science solutions using AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
• Work with technologies such as Python, SQL, Spark, Databricks, MLflow, TensorFlow, PyTorch, and Scikit-learn.
• Evaluate and recommend data science, AI/ML, and cloud technologies based on scalability, performance, security, and cost.
• Ensure data quality, governance, security, privacy, and compliance requirements are incorporated into solution architecture.
• Design solutions supporting real-time and batch data processing.
• Establish architecture patterns for APIs, microservices, model serving, and integration with enterprise applications.
• Monitor and optimize model performance, scalability, reliability, and resource utilization.
• Provide technical leadership and mentorship to Data Scientists, ML Engineers, Data Engineers, and development teams.
• Work with stakeholders to translate business requirements into technical and data-driven solutions.
• Create architecture diagrams, technical documentation, standards, and solution design specifications.
• Stay current with emerging technologies in AI, Machine Learning, Generative AI, Data Science, and Cloud Computing.

Skills

Data Science Architecture

ML Architecture

AI Architecture

Python

SQL

Spark / PySpark

Databricks

MLflow

TensorFlow

PyTorch

Tools

Scikit-learn

TensorFlow

PyTorch

XGBoost

Docker

Kubernetes

AWS

Azure

Google Cloud Platform

Spark

Job description

Machine Learning Technologies, LLC is seeking an experienced Data Science Architect to design, architect, and lead scalable data science, ML, and AI solutions for enterprise applications. You will work with data scientists, engineers, and business stakeholders to establish scalable architecture, standards, and best practices.

The role emphasizes MLOps, model deployment, and cloud platforms (AWS, Azure, GCP) with hands-on work in Python, SQL, Spark, Databricks, and ML frameworks.