Junior AI/ML Engineer (Data & Cloud Platforms)

About the role

As aJunior AI/ML Engineer (Data & Cloud Platforms) with 1–2 years of experience, you will support the development of scalable data systems and contribute to AI and machine learning initiatives.This role combinesdata engineering, cloud technologies, and machine learning implementationto help build intelligent data-driven solutions.

You will work withAWS, GCP, and Azure cloud services, integrate with CRM and marketing platforms, and support analytics and AI solutions through tools such asGoogle Looker and Tableau. The role will involve working with both data pipelines and machine learning workflows to enable advanced analytics and automation.

The positionoperatesunder ahybrid work model, requiringin-office presence at the Dallas, TX location two days per week, with the remaining days worked remotely.

What you'll do

Data Pipeline Development

Assist in designing, developing, andmaintainingscalableETL/ELT pipelinesacross cloud platforms such asGCP, AWS, and Azure, using services likeDataflow, Cloud Composer (Airflow), Azure Synapse, and AWS Data Pipelines.

Data Integration

Work with structured and unstructured data sources, includingCRM systems, marketing platforms, APIs, and internal business systems, to support analytics and AI-driven applications.

Database Management

Develop andoptimizequeries forSQL and NoSQL databasessuch asTeradata,BigQuery, Cassandra, and cloud data warehouses.

Machine Learning Implementation

Support the development and deployment of machine learning models usingPython and data science libraries (Pandas, NumPy, Scikit-learn)and cloud AI services such asGCP Vertex AI, AWS SageMaker, or Azure ML.

AI-Enabled Data Workflows

Assist in building data pipelines that supportpredictive analytics, automation, and AI-driven insights.

Data Visualization

Build andmaintaindashboards usingGoogle Looker and Tableauto help business and marketing teams understand and act on data insights.

Collaboration

Work closely withdata engineers, analysts, data scientists, and marketing teamsto understand business requirements and support the development of data and AI solutions.

Required Qualifications

Cloud Platforms

Hands-on experience withGCP, AWS, or Azure, particularly in data engineering or machine learning environments.

Programming Skills

StrongproficiencyinPythonwith experience using data processing and machine learning libraries such asPandas, NumPy, and Scikit-learn.

Database Experience

Experience working withSQL and NoSQL databases, including platforms such asBigQuery, Teradata, Cassandra, or similar technologies.

Data Visualization

Experience building dashboards and reports usingGoogle Looker or Tableau.

Machine Learning Knowledge

Basic understanding ofmachine learning workflows, model training, evaluation, and deployment in cloud environments.

Data Automation & Transformation

Experience withAlteryx or similar toolsfor workflow automation and data preparation.

Preferred Qualifications

Experience withdata warehousing platformssuch asSnowflake or Redshift.

Exposure toApache Spark, Airflow, or other orchestration tools.

Familiarity withMLOpspractices and cloud-based ML platforms.

Understanding ofdata governance, security, and compliance practices.

Relevant certifications such asGoogle Cloud Professional Data Engineer or Machine Learning certifications.

Mod Op, LLC provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.