Job description
Gorilla Logic provides nearshore Agile teams to Fortune 500 and SMB companies, bringing unparalleled expertise in the delivery of full-stack web, mobile, and enterprise applications. Our highly collaborative Agile Gorillas are uniquely qualified to implement complex software initiatives. With offices in the United States, Costa Rica, Colombia and Mexico, Gorilla Logic helps clients gain competitive advantages to achieve results faster.
Lead AI Engineer / Expert AI Solutions Architect
Overview
We are seeking a highly experienced Lead AI Engineer to spearhead the creation, training, and deployment of advanced AI models that directly solve complex business challenges. This role is critical in applying cutting-edge machine learning and data science techniques to deliver scalable, production-ready AI solutions that drive measurable impact and align with organizational strategy.
Key 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.
Core Skills
*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
Supporting Skills
*Data Preparation and Feature Engineering
*Model Development & Hyperparameter Optimization
*Performance Analysis and Root-Cause Debugging
Technical Enablers & Tools
*AI Frameworks: TensorFlow, PyTorch
*Development Environments: Jupyter Notebooks, Google Colab
*Version Control: Git, DVC
*Compute Infrastructure: GPUs, TPUs
*AI Platforms: AWS SageMaker, Azure ML
*Infrastructure Management: Docker, Kubernetes for ML
*Data Security: Role-based access, encryption standards in AI systems
Preferred Qualifications
*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.
