Junior AI​/ML Engineer; Data & Cloud Platforms

Position: Junior AI/ML Engineer (Data & Cloud Platforms)

About the role

As a Junior 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 combines data engineering, cloud technologies, and machine learning implementation to help build intelligent data-driven solutions.

You will work with AWS, GCP, and Azure cloud services

, integrate with CRM and marketing platforms, and support analytics and AI solutions through tools such as Google Looker and Tableau

. The role will involve working with both data pipelines and machine learning workflows to enable advanced analytics and automation.

The position operates under a hybrid work model

, requiring in-office presence at the Dallas, Texas location two days per week

, with the remaining days worked remotely.

What you’ll do

Assist in designing, developing, and maintaining scalable ETL/ELT pipelines across cloud platforms such as GCP, AWS, and Azure

, using services like Dataflow, Cloud Composer (Airflow), Azure Synapse, and AWS Data Pipelines

.

Data Integration

Work with structured and unstructured data sources, including CRM systems, marketing platforms, APIs, and internal business systems

, to support analytics and AI-driven applications.

Database Management

Develop and optimize queries for SQL and No

SQL databases such as Teradata, Big Query, Cassandra, and cloud data warehouses

.

Support the development and deployment of machine learning models using Python and data science libraries (Pandas, Num Py, Scikit-learn) and cloud AI services such as GCP Vertex AI, AWS Sage Maker, or Azure ML

.

AI-Enabled Data Workflows

Assist in building data pipelines that support predictive analytics, automation, and AI-driven insights

.

Build and maintain dashboards using Google Looker and Tableau to help business and marketing teams understand and act on data insights.

Work closely with data engineers, analysts, data scientists, and marketing teams to understand business requirements and support the development of data and AI solutions.

Required Qualifications

Hands‑on experience with GCP, AWS, or Azure

, particularly in data engineering or machine learning environments.

Programming Skills

Strong proficiency in Python with experience using data processing and machine learning libraries such as Pandas, Num Py, and Scikit-learn

.

Database Experience

Experience working with SQL and No

SQL databases

, including platforms such as Big Query, Teradata, Cassandra, or similar technologies

.

Experience building dashboards and reports using Google Looker or Tableau

.

Basic understanding of machine learning workflows, model training, evaluation, and deployment in cloud environments

.

Data Automation & Transformation

Experience with

Alteryx or similar tools for workflow automation and data preparation.

Preferred Qualifications

Experience with

data warehousing platforms such as Snowflake or Redshift

.

Exposure to Apache Spark, Airflow, or other orchestration tools

.

Familiarity with MLOps

practices and cloud-based ML platforms

.

Understanding of data governance, security, and compliance practices

.

Relevant certifications such as Google 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.

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