AI Architect

• Proficiency in AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers.

• Experience with Generative AI technologies and large language models (e.g., GPT-4, BERT, DALL-E).

• Expertise in cloud-native AI services:

o Azure: Azure Machine Learning, Cognitive Services, OpenAI Service

o AWS: Sage Maker, Bedrock, Rekognition

o Google Cloud: Vertex AI, Auto ML, Generative AI Studio

• Hands-on experience with MLOps practices, including CI/CD for model deployment, model monitoring, and retraining.

• Knowledge of utility-specific protocols, systems, and data types (e.g., SCADA, AMI, GIS).

Soft Skills

• Strong problem-solving skills, with the ability to translate business challenges into AI solutions.

• Excellent communication and stakeholder management skills, with the ability to present technical concepts to non-technical audiences.

Certifications

• Relevant certifications in AI/ML and cloud platforms:

o Azure AI Engineer Associate

o AWS Certified Machine Learning Specialty

o Google Professional Machine Learning Engineer

• Certifications in Generative AI tools (e.g., OpenAI or Hugging Face) are a plus.

Preferred Skills:

• Knowledge of emerging trends in the utilities industry, such as energy transition, smart grids, and renewable energy integration.

• Experience with AI/ML applications in IoT and edge computing for utilities.

• Familiarity with AI frameworks for sustainability and carbon footprint reduction.

Experience Required            
• 8+ years in AI/ML architecture, with at least 5 years focused on Power & Utilities.

• Proven track record of deploying AI solutions at scale in enterprise environments