[Remote] Applied AI Engineer

Note: The job is a remote job and is open to candidates in USA. Insight Global is seeking an Applied AI/ML Engineer (Data Scientist) to build the intelligence layer of a mission-critical platform supporting renewable energy generation, electrical transmission, and grid operations. The role develops and deploys production-ready AI, machine learning, generative AI, and advanced analytics solutions for anomaly detection, asset reliability, troubleshooting, operational decision support, and optimization.

Responsibilities

• Design, develop, evaluate, and deploy AI and machine learning solutions supporting renewable energy and electric transmission operations
• Develop predictive models and advanced analytics for asset health monitoring, anomaly detection, forecasting, reliability analysis, fault identification, and operational optimization
• Build generative AI and agent-based solutions using enterprise-approved large language models (LLMs) and AI platforms
• Develop AI-powered systems that assist engineers and operators with troubleshooting, knowledge retrieval, incident analysis, and operational decision support
• Design prompts, agents, tools, workflows, and orchestration patterns to improve workforce productivity and access to institutional knowledge
• Develop Retrieval-Augmented Generation (RAG) solutions that leverage engineering documentation, operating procedures, technical drawings, maintenance records, and operational data
• Create rigorous evaluation frameworks to measure model and agent performance
• Define and monitor metrics related to accuracy, relevance, reliability, hallucination rates, latency, business impact, and operational cost
• Implement AI governance controls, validation mechanisms, and guardrails to ensure trustworthy and compliant AI outputs
• Partner with Data Engineering teams to define data ingestion, feature engineering, training, retrieval, and inference requirements
• Collaborate with Cloud and Software Engineering teams to deploy scalable AI services into production environments
• Rapidly prototype innovative AI solutions while maintaining a clear path toward enterprise deployment
• Continuously monitor model performance and drive optimization efforts post-deployment
• Communicate analytical findings and AI-driven insights to engineers, operations teams, product stakeholders, and leadership
• Stay current on advancements in machine learning, generative AI, agentic AI, energy analytics, and utility technology

Skills

• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Machine Learning, Mathematics, or a related discipline, or equivalent professional experience
• 4+ years of experience developing machine learning, artificial intelligence, or advanced analytics solutions
• Strong programming experience with Python
• Experience with machine learning and data science frameworks such as Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, or similar technologies
• Experience deploying AI/ML solutions into production environments
• Strong foundation in statistics, predictive modeling, experimentation, model evaluation, and data analysis
• Experience working in cloud-based data and compute environments such as AWS, Azure, or Google Cloud Platform
• Experience developing APIs and working within modern software development practices, source control, and CI/CD pipelines
• Demonstrated ability to translate complex business, engineering, or operational challenges into analytical solutions
• Strong communication and stakeholder management skills
• Experience with Large Language Models (LLMs), Generative AI, Agentic AI, and RAG architectures
• Experience supporting utility, renewable energy, power generation, electrical transmission, grid modernization, energy trading, or industrial operations environments
• Familiarity with operational technology (OT), SCADA systems, telemetry data, asset management systems, or utility operations
• Experience analyzing time-series, sensor, equipment, or operational data
• Knowledge of MLOps, AI governance, model monitoring, and responsible AI practices
• Experience building intelligent solutions that support reliability, maintenance, outage management, asset performance, or grid operations

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