Artificial Intelligence Engineer
7 days ago
An AI Engineer designs, develops, and implements artificial intelligence solutions by creating complex algorithms and machine learning models to solve business challenges. Key responsibilities include building and managing AI infrastructure, sourcing and analyzing data, fine-tuning models for performance, integrating AI solutions into applications via APIs, and collaborating with data scientists, developers, and business stakeholders. This role requires a strong foundation in software development, data science, programming (especially Python), cloud computing, and mathematics like statistics and calculus. Key Responsibilities
- Model Development: Design, build, and train complex algorithms and machine learning models for specific business problems.
- Infrastructure Management: Create and maintain the AI development and production infrastructure, including setting up scalable environments and managing data pipelines.
- Data Analysis: Conduct statistical analysis, interpret data, and use these insights to guide and optimize AI models.
- Deployment & Integration: Deploy AI solutions into production, ensuring they are integrated into existing systems and applications using APIs.
- Performance Optimization: Monitor, evaluate, and fine-tune AI models to improve accuracy, efficiency, and overall performance.
- Collaboration: Work with cross-functional teams (data scientists, software developers, product managers) to understand requirements and deliver solutions.
- Technical Expertise: Provide guidance and share knowledge on AI-related projects and best practices within the organization.
Essential Skills & Qualifications
- Technical Skills: Proficiency in programming languages like Python, deep learning frameworks, and cloud platforms (AWS, Azure, GCP).
- Data Science Fundamentals: Strong understanding of machine learning, data analysis, and data engineering concepts.
- Software Engineering: Ability to write clean, efficient, and reusable code.
- Mathematics: Solid knowledge of linear algebra, probability, and statistics.
- Analytical Thinking: Strong analytical skills to interpret data and find solutions to complex problems.
- Problem-Solving: Ability to identify, assess, and resolve issues within AI systems.
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