Junior AI/ML Engineer (Data & Cloud Platforms)

Mod Op; Dallas (TX); Hybrid; USD 70,000 - 95,000; Full time

Benefits offered by this job

Hybrid work model

Health insurance options

Job summary

Mod Op is seeking a Junior AI/ML Engineer (Data & Cloud Platforms) in Dallas with 1-2 years of experience to support scalable data systems and AI initiatives. You will work across AWS, GCP, and Azure, integrating CRM and marketing data while contributing to analytics and automation.

The role combines data engineering, cloud tech, and ML, requiring collaboration with engineers and marketing teams; it follows a hybrid model with in-office presence in Dallas two days per week.

Qualifications

• Cloud platforms experience (GCP/AWS/Azure).
• Python with data processing and ML libraries (Pandas, NumPy, Scikit-learn).
• SQL/NoSQL experience (BigQuery, Teradata, Cassandra).
• Experience building dashboards in Looker or Tableau.
• Basic understanding of ML workflows, training, evaluation, deployment.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines across cloud platforms.
• Integrate data from CRM systems, marketing platforms, APIs, and internal systems.
• Develop queries for SQL/NoSQL databases and cloud data warehouses.
• Support ML model development and deployment in cloud environments.
• Build and maintain dashboards to aid business insights.

Skills

Python

Cloud platforms

Data engineering

SQL/NoSQL

Looker/Tableau

Education

Bachelor's degree in Computer Science or related

Tools

GCP

AWS

Azure

BigQuery

Tableau/Looker

Pandas/NumPy/Scikit-learn

Job description

About this position

About Mod Op

Mod Op is a full-service advertising agency able to offer clients a full suite of solutions. Mod Op can offer you access to low-cost, high-quality health care options and a team of enthusiastic, collaborative and motivated coworkers who see career development and personal development as intertwined.

At Mod Op, we're more than just an agency, we're a team of forward-thinking professionals who are passionate about driving client success. We believe in fostering meaningful relationships, collaborating across disciplines, and delivering impactful solutions that help businesses grow. If you are a strategic thinker with a passion for building lasting client partnerships, we'd love to hear from you. Join us and be part of a company that values innovation, creativity, and excellence in everything we do.

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

What you'll do

Data Pipeline Development:
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 NoSQL databases such as Teradata, BigQuery, Cassandra, and cloud data warehouses.

Machine Learning Implementation:
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.

AI-Enabled Data Workflows:
Assist in building data pipelines that support predictive analytics, automation, and AI-driven insights.

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

Collaboration:
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

Cloud Platforms:
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, NumPy, and Scikit-learn.

Database Experience:
Experience working with SQL and NoSQL databases, platforms such as BigQuery, Teradata, Cassandra, or similar technologies.

Data Visualization:
Experience building dashboards and reports using Google Looker or Tableau.

Machine Learning Knowledge:
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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