Text copied to clipboard!
Title
Text copied to clipboard!AI Platform Engineer
Description
Text copied to clipboard!
We are looking for an AI Platform Engineer to join our team and help build scalable, efficient, and robust AI infrastructure. As an AI Platform Engineer, you will be responsible for designing, developing, and maintaining AI platforms that support machine learning models, data pipelines, and cloud-based AI services. You will work closely with data scientists, software engineers, and DevOps teams to ensure seamless integration and deployment of AI solutions.
Your role will involve optimizing AI workflows, automating model deployment, and ensuring the reliability and scalability of AI systems. You will also be responsible for implementing best practices in MLOps, monitoring system performance, and troubleshooting issues as they arise. A strong understanding of cloud computing, containerization, and distributed computing is essential for this role.
In this position, you will have the opportunity to work with cutting-edge AI technologies and contribute to the development of innovative AI-driven applications. You will play a key role in shaping the AI infrastructure and ensuring that AI models are deployed efficiently and securely. If you are passionate about AI, cloud computing, and automation, we encourage you to apply and be part of our dynamic team.
Responsibilities
Text copied to clipboard!- Design and develop scalable AI platforms for machine learning model deployment.
- Implement and maintain MLOps best practices for continuous integration and deployment.
- Optimize AI workflows and automate model training and deployment processes.
- Ensure the reliability, security, and scalability of AI infrastructure.
- Collaborate with data scientists and software engineers to integrate AI solutions.
- Monitor system performance and troubleshoot issues in AI pipelines.
- Manage cloud-based AI services and containerized environments.
- Stay updated with the latest advancements in AI and cloud technologies.
Requirements
Text copied to clipboard!- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Proficiency in programming languages like Python, Java, or Scala.
- Knowledge of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
- Experience with machine learning frameworks such as TensorFlow or PyTorch.
- Understanding of distributed computing and big data technologies.
- Strong problem-solving skills and ability to work in a collaborative environment.
- Excellent communication and documentation skills.
Potential interview questions
Text copied to clipboard!- Can you describe your experience with MLOps and AI platform development?
- How have you optimized AI workflows in your previous roles?
- What cloud platforms have you worked with, and how have you used them for AI deployment?
- Can you explain a challenging AI infrastructure problem you solved?
- What strategies do you use to ensure the scalability and reliability of AI systems?
- How do you stay updated with the latest AI and cloud computing technologies?
- Describe a time when you collaborated with data scientists and engineers on an AI project.
- What tools and frameworks do you prefer for managing AI pipelines?
