Junior AI/ML Engineer (Data & Cloud Platforms)

Mod Op • Dallas, TX

2d • Hybrid

About The Position

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, TX location two days per week, with the remaining days worked remotely.

Requirements

• Hands-on experience with GCP, AWS, or Azure, particularly in data engineering or machine learning environments.
• Strong proficiency in Python with experience using data processing and machine learning libraries such as Pandas, NumPy, and Scikit-learn.
• Experience working with SQL and NoSQL databases, including platforms such as BigQuery, 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.
• Experience with Alteryx or similar tools for workflow automation and data preparation.

Nice To Haves

• 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.

Responsibilities

• 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.
• Work with structured and unstructured data sources, including CRM systems, marketing platforms, APIs, and internal business systems, to support analytics and AI-driven applications.
• Develop and optimize queries for SQL and NoSQL databases such as Teradata, BigQuery, Cassandra, and cloud data warehouses.
• Support the development and deployment of machine learning models using Python and data science libraries (Pandas, NumPy, Scikit-learn) and cloud AI services such as GCP Vertex AI, AWS SageMaker, or Azure ML.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed