Trainee Edge Ai Machine Learning Jobs in Florida

Summary:

The Senior Director of Machine Learning and Artificial Intelligence will be a strategic leader responsible for driving the development and execution of our machine learning and broader artificial intelligence initiatives. This individual will lead a team of machine learning engineers, AI engineers, and researchers to build and deploy cutting-edge ML models and AI solutions that create business value and enhance our products and services. 

The ideal candidate will have a strong technical background in machine learning and artificial intelligence, extensive leadership experience, and a proven track record of delivering impactful enterprise-grade AI solutions. This role requires working closely with business partners while understanding and working within the constraints of the business to maintain a competitive technological edge.

Duties and Responsibilities:

• Team Leadership: Lead and mentor a team of machine learning and AI engineers, fostering a culture of innovation, continuous learning, and excellence. 
• Strategic Roadmap: Define and execute the comprehensive ML/AI strategy and roadmap, aligning it with the company's overall business objectives and long-term vision. 
• End-to-End Deployment: Oversee the end-to-end development and deployment of machine learning and artificial intelligence models, from ideation and experimentation to production and monitoring.
• Cross-Functional Collaboration: Collaborate with product, engineering, data platform, and other cross-functional teams to identify new opportunities for leveraging traditional ML and advanced AI. 
• AI Innovation & Adoption: Stay up-to-date with the latest advancements in machine learning and AI (including Generative AI, Large Language Models, and computer vision), and drive the adoption of new technologies and best practices. 
• AI Governance & Ethics: Establish and champion frameworks for responsible AI, ethics, data privacy, and compliance across all model deployments.
• Stakeholder Communication: Communicate the complex value and business impact of machine learning and AI initiatives to senior leadership, C-suite executives, and other stakeholders. 
• Roadmap Influence: Influence product and operational roadmaps with actionable data insights and active AI deployments. 
• Data Strategy: Build a strategic learning roadmap based on data observations, strategic imperatives, and developed hypotheses, while managing robust data and feature pipelines. 
• Education: Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field. 
• Domain Experience: 10+ years of experience in machine learning and AI, with a proven track record of building, scaling, and deploying production-level models. 
• Leadership Experience: 5+ years of experience leading and managing high-performing machine learning or AI engineering and research teams. 
• Technical Expertise: Deep expertise in a variety of machine learning and AI techniques, including deep learning, natural language processing (NLP), reinforcement learning, and Generative AI/Large Language Models (LLMs). 
• Programming & Frameworks: Strong programming skills in Python and deep experience with ML/AI frameworks such as TensorFlow, PyTorch, or Hugging Face. 
• Core Skills: Excellent leadership, communication, and project management skills. 
• Organizational Scaling: Demonstrated success in building and scaling ML/AI organizations from the ground up, including hiring, budgeting, and tool/vendor selection.     
• Executive Presence: Proven ability to link ML and AI initiatives to P&L outcomes, with experience presenting comprehensive AI strategies to C-suite executives or Board members. 
• Infrastructure Knowledge: High-level architectural understanding of MLOps, LLMOps, cloud infrastructure (AWS/GCP/Azure), and the full model development lifecycle (MDLC). 

Minimum Qualifications:

Communication Skills:

• Writing, Talking/Hearing on the phone (Continually=67-100% of workday)

Environment Requirements: 

• Remote/Home office (Continually=67-100% of the workday)

Travel:

• Occasionally, less than 25%