AI Application Associate II

About Us

SoCalGas, the nation’s largest gas distribution utility, is dedicated to providing safe, reliable, and affordable energy to over 21 million Southern California customers. Through innovation, collaboration, and an unwavering commitment to the needs of our communities we proudly uphold our mindset of “Glad to be of Service” and  provide exceptional customer service today and ready to meet California’s energy needs with innovative solutions for tomorrow.  

As an employee of SoCalGas, you will support our core values to do the right thing, champion people, and shape the future. You will play a pivotal role in the energy transition initiatives, supporting our mission: Safe, reliable, and affordable energy delivery today. Ready for tomorrow.  We are committed to attracting top talent and fostering a diverse workforce that reflects the vibrant communities we serve.   

As an employee of SoCalGas, you’ll enjoy a competitive compensation plan, upward mobility opportunities and the ability to find a true work life balance.  Discover the rewards of joining SoCalGas by exploring our website: Our Mission; Sustainability, In the Community, and Employee Benefits. Join SoCalGas today and become a vital part of a team that is driving innovation, championing community needs, and shaping the future of energy in California. 

Primary Purpose 

Contributes to artificial intelligence (AI) application development by performing data analysis, refining models, and integrating solutions under guidance, ensuring accuracy and reliability in early-stage deployments.

Duties and Responsibilities

• Develops and modifies artificial intelligence applications using standard frameworks and programming interfaces.

• Conducts feature engineering and data preprocessing to improve model accuracy and robustness.

• Implements and tunes machine learning algorithms for tasks such as classification or clustering.

• Participates in code reviews and contributes to improving development practices and documentation.

• Collaborates with software engineers to deploy models in production environments using containerization tools.

• Monitors model performance and assists in troubleshooting issues in deployed systems.

• Applies ethical and compliance standards in artificial intelligence development.

• Communicates technical findings to peers in a clear and concise manner.

• Performs other duties as assigned.

Education

• Typically requires a 4 year degree in a relevant field, or equivalent combination of relevant education and experience

Experience

• Typically requires 2 years of related experience.

Knowledge, Skills and Abilities

• Artificial Intelligence/Machine Learning - Applies knowledge of artificial intelligence and machine learning from a data perspective and understands potential data applications to improve overall business outcomes.
• Statistical Modeling - Uses data science methods to apply statistical analysis to datasets in a strategic manner, producing intuitive visualizations that aid in identifying relationships between variables and making predictions.
• Programming Languages - Proficiency in applied AI and machine learning programming, enabling the development of end-to-end solutions such as feature engineering, model development, performance tuning, and deployment of intelligent systems.
• Data Structures and Algorithms - Knowledge of efficient data handling, algorithmic complexity, and optimization techniques.
• Domain-Specific Knowledge - Understanding of the industry where AI is applied (e.g., healthcare, finance, robotics) for contextual solutions.
• Data Preprocessing and Feature Engineering - Ability to clean, transform, and prepare data for model training.
• AI Prompt Engineering - Demonstrates the ability to ethically and effectively design, refine, and evaluate structured prompts that enable artificial intelligence systems to generate accurate, relevant, and business-aligned outputs, applying critical thinking, sound judgment, and digital fluency to support organizational goals.
• Problem-Solving and Critical Thinking - Ability to translate business problems into AI solutions and troubleshoot complex issues.
• Communication and Visualization - Ability to explain technical concepts to non-technical stakeholders and present insights clearly.
• Continuous Learning and Adaptability - Staying updated with emerging AI trends, tools, and ethical considerations.