Lead AI Engineer

Summary

Join Gorilla Logic as a Lead AI Engineer/Expert AI Solutions Architect to spearhead the creation, training, and deployment of advanced AI models. You will apply cutting-edge machine learning and data science techniques to deliver scalable, production-ready AI solutions. This critical role involves leading end-to-end AI model development, architecting machine learning pipelines, optimizing model performance, and implementing best practices in AI development. You will guide and mentor teams, ensure robust version control, and collaborate cross-functionally. The ideal candidate will have extensive experience in AI engineering and a deep understanding of AI development environments and frameworks.

Requirements

• AI Development Best Practices
• AI Model Lifecycle Management
• AI Model Training Optimization
• Prompt Engineering
• Version Control for AI Models (e.g., Git)
• Automated Testing & Validation Tools for AI
• Collaborative AI Development Platforms
• Deep understanding of AI Development Environments & Frameworks

Responsibilities

• Lead end-to-end development of AI models, from data preparation and training to deployment and lifecycle management
• Architect scalable machine learning pipelines and frameworks tailored to business use cases
• Optimize model performance through rigorous training, validation, and tuning strategies
• Implement best practices in AI development across environments, frameworks, and collaborative workflows
• Champion the use of automated testing, validation, and monitoring tools for production-grade AI
• Guide and mentor teams on prompt engineering techniques and model refinement for generative and predictive AI use cases
• Ensure robust version control for AI models, integrating tools like Git with ML workflows
• Collaborate cross-functionally with data engineering, product, and DevOps teams to ensure alignment and scalability
• Maintain security, compliance, and performance across AI infrastructure and data systems

Preferred Qualifications

• Data Preparation and Feature Engineering
• Model Development & Hyperparameter Optimization
• Performance Analysis and Root-Cause Debugging
• 6+ years in machine learning, AI engineering, or applied data science roles
• Proven experience deploying models in production at scale
• Strong knowledge of MLOps and AI/ML governance practices
• Advanced degree (MS/PhD) in Computer Science, Artificial Intelligence, or a related field is a plus