Ai Arquitect (Inglés Avanzado) | Traslado A España

1. AI Strategy & Roadmap Development · Define the AI vision, strategy, and roadmap aligned with business goals · Identify opportunities to leverage AI/ML to solve business challenges and improve efficiency · Stay updated on emerging AI trends, tools, and technologies to drive innovation 2. Architecture Design & Development · Design and implement scalable, efficient, and secure AI/ML architectures · Define best practices for AI model development, deployment, and monitoring · Ensure seamless integration of AI solutions with existing systems, platforms, and workflows 3. Collaboration & Stakeholder Engagement · Work with data scientists, engineers, and software developers to design and deploy AI models · Collaborate with business leaders to translate requirements into AI-driven solutions · Act as a technical advisor to stakeholders, providing guidance on AI capabilities and limitations. 4. Data Management & Preparation · Oversee data collection, preprocessing, and transformation to ensure high-quality inputs for AI models · Work with data teams to establish data pipelines and ensure data availability for AI initiatives. · Promote data governance and compliance with data privacy regulations (e.g., GDPR, CCPA). 5. AI Model Deployment & Optimization · Lead the deployment of AI models into production environments, ensuring scalability and reliability. · Optimize AI models for performance, accuracy, and efficiency. · Implement monitoring and feedback mechanisms to continuously improve AI solutions. 6. Governance & Ethical AI Practices · Mitigate risks associated with AI, including bias, security vulnerabilities, and unintended consequences. · Ensure compliance with regulatory requirements and industry standards for AI. 7. Leadership & Mentorship · Provide technical leadership and mentorship to AI and data teams · Promote knowledge sharing and foster a culture of innovation within the organization.

Education · Bachelor’s or Master’s in Computer Science, Data Science, AI, or related field Experience · Proven experience in AI/ML architecture, data science, or related field · Hands-on experience designing and deploying AI/ML models in production environments. · Strong understanding of AI/ML frameworks, libraries, and tools (e.g., TensorFlow, PyTorch, scikit-learn). · Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. · Familiarity with big data technologies (Hadoop, Spark) and data engineering workflows Technical Skills · Proficiency in programming languages such as Python, R, or Java. · trong knowledge of AI/ML algorithms, deep learning, natural language processing (NLP), and computer vision. · Expertise in model lifecycle management, including MLOps practices. · Understanding of containerization and orchestration tools (e.g., Docker, Kubernetes). · Knowledge of data visualization tools and techniques. Soft Skills · Excellent problem-solving and analytical abilities · Strong communication and presentation skills for non-technical stakeholders · Leadership and team management · Strategic thinking focused on delivering business value Preferred Qualifications · Certification in AI/ML or cloud platforms (e.g., AWS Certified Machine Learning, Google Professional ML Engineer). · Experience with edge AI, federated learning, or real-time AI applications. · Knowledge of ethical AI practices and frameworks. · Familiarity with Agile and DevOps methodologies.