AI Integration Engineer

🕒 April 13

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Creative Chaos

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2000

🤝 B2B

☁️ SaaS

⚡ Productivity

B2B • SaaS • Productivity

Creative Chaos is an innovation delivery agency that partners with businesses of all sizes to develop and bring products to market. They focus on creating user-centered experiences and translating consumer insights into innovative products. They offer services such as team augmentation, MVP (Minimum Viable Product) development, and DevOps and cloud solutions to help businesses innovate, develop, and deliver products efficiently. Creative Chaos acts as an extension to their clients' teams, providing support and expertise throughout the product development process.

📋 Description

• Integrate AI and machine learning models into production environments and business applications. • Collaborate with data scientists, software engineers, and product teams to design integration strategies. • Develop APIs, middleware, and interfaces to enable seamless AI model deployment and usage. • Ensure the scalability, reliability, and performance of AI integrations in real-world applications. • Monitor and troubleshoot AI system performance, identifying and resolving integration issues. • Optimize AI workflows and data pipelines to improve efficiency and accuracy. • Maintain documentation related to integration processes, architectures, and configurations. • Stay updated with emerging AI technologies and recommend new integration approaches. • Support the deployment and maintenance of AI-based solutions across various platforms.

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. • 3+ years of experience in integrating AI/ML models into production systems. • Strong programming skills in Python, Java, or similar languages. • Experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. • Familiarity with API development, RESTful services, and microservices architecture. • Knowledge of cloud platforms and deployment tools (AWS, Azure, Google Cloud). • Understanding of data pipelines, ETL processes, and data engineering concepts. • Ability to troubleshoot and optimize AI integration performance. • Excellent communication and collaboration skills. • Proactive attitude towards learning new technologies and continuous improvement.