Machine Learning Engineer 3 4P/392

4P Consulting Inc.; Atlanta (GA); On-site; USD 110,000 - 130,000; Full time

Job summary

A consulting firm is seeking a highly skilled Machine Learning Engineer (Level 3) with 5–10 years of experience. The role involves designing, developing, and deploying advanced AI models specifically for the utilities and energy sector. Candidates should have a strong background in machine learning, data analysis, and model deployment. Preferred qualifications include industry experience in utilities or energy, and proficiency in tools like Python and TensorFlow. This position offers the chance to innovate and optimize business operations.

Qualifications

• 5–10 years of experience in AI, ML, or data science roles.
• Proven success in AI model development and deployment.

Responsibilities

• Design and implement machine learning models for utility-specific challenges.
• Analyze large datasets from SCADA, AMI, and IoT systems.
• Train, test, and validate AI models.
• Deploy AI solutions into production systems.
• Monitor AI models for performance and compliance.

Skills

Machine learning

Data analysis

AI model development

Collaboration

Problem-solving

Communication Skills

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics

Tools

Python

R

Java

TensorFlow

PyTorch

scikit-learn

Azure ML

Azure Databricks

Job description

Job Summary

We are seeking a highly skilled Machine Learning Engineer (Level 3) with 5–10 years of experience to design, develop, and deploy advanced AI models and systems. This role requires expertise in machine learning, data analysis, and model deployment to optimize business operations and drive innovation within the utilities and energy sector.

The successful candidate will collaborate with cross-functional teams—including data scientists, engineers, and business stakeholders—to integrate AI solutions into real-world applications that support operational efficiency, customer service, and sustainability initiatives.

Key Responsibilities

• AI Model Development: Design and implement machine learning models and algorithms to address utility-specific challenges such as grid optimization, asset reliability, predictive maintenance, and customer analytics.
• Data Analysis: Analyze large, complex datasets from SCADA, AMI, and IoT systems to extract actionable insights.
• Model Training & Evaluation: Train, test, and validate AI models to ensure accuracy, scalability, and compliance with industry reliability standards.
• Deployment & Integration: Deploy AI solutions into production systems and integrate with enterprise platforms (e.g., Azure, Maximo, EMS/DMS systems).
• Innovation: Stay current with the latest advancements in AI/ML and recommend solutions that can enhance grid resilience, safety, and efficiency.
• Collaboration: Partner with engineering, IT, and business units to define requirements and deliver business-aligned AI solutions.
• Performance Monitoring: Continuously monitor AI models and refine as needed to maintain performance and compliance.
• Documentation & Knowledge Sharing: Create clear documentation of models, workflows, and processes for reuse and compliance.

Qualifications

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.

Experience:

• 5–10 years of experience in AI, ML, or data science roles, with proven success in AI model development and deployment.
• Industry experience in utilities, energy, or large-scale infrastructure data is preferred.

Technical Skills:

• Proficiency in Python, R, or Java.
• Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn.
• Strong grasp of data structures, algorithms, and applied statistics.
• Familiarity with cloud platforms such as Azure ML and Azure Databricks (preferred), AWS or Google Cloud (a plus).
• Experience with big data tools (e.g., Spark, Hadoop) is desirable.
• Exposure to natural language processing (NLP) or computer vision a plus.

Soft Skills:

• Strong analytical and problem-solving abilities.
• Excellent communication skills for cross-functional collaboration.
• Ability to work independently and manage multiple projects simultaneously.
• Experience working in agile or iterative development environments.

Preferred Qualifications

• Lighting up AI/ML use cases in the utility/energy sector (e.g., outage prediction, DERMS optimization, vegetation management analytics).
• Certifications in AI/ML, data science, or cloud platforms (Azure, AWS, GCP).
• Experience with MLOps pipelines and CI/CD integration for model deployment.