Role:
As a pivotal member of the AI team, the Cloud Infrastructure, DevOps & Software Engineer will undertake a multi-dimensional role, merging the worlds of infrastructure management, software development, and AI-centric operations. The individual will be responsible for architecting, deploying, and managing the cloud infrastructure that powers our AI models, while concurrently participating in the development, monitoring and maintenance of Python-based applications integral to our AI endeavors. Seamless collaboration with AI engineers, data scientists, and other developers is crucial for success in this hybrid role.
Key Responsibilities:
1. AI Infrastructure Management: Design, implement, and maintain the cloud-based infrastructure tailored for the AI team’s needs, ensuring optimal performance and scalability for AI models and tasks.
2. AI Software Development: Develop, test, and enhance Python-based applications integral to the AI operations, focusing on efficiency, scalability, and modularity.
3. AI Model Deployment: Collaborate with data scientists to seamlessly integrate, deploy, and scale AI models in cloud environments.
4. Infrastructure as Code (IAC): Apply IAC practices for automating and managing AI infrastructure using tools such as Terraform, CloudFormation, or similar.
5. Continuous Integration & Deployment: Establish and manage CI/CD pipelines tailored for AI applications and models.
6. AI System Monitoring: Set up monitoring tools to gauge the health and performance of AI models and applications in real-time.
7. Collaboration: Actively participate in architectural and strategic discussions with AI researchers, data scientists, and other stakeholders.
8. AI Security: Enforce security best practices specific to AI, safeguarding data, models, and infrastructure.
9. Troubleshooting: Swiftly diagnose and rectify issues related to AI applications, infrastructure, or model deployments.
10. Continuous Learning: Stay abreast with the latest advancements in AI, cloud computing, software development best practices, and DevOps methodologies.
Skills Required:
1. Technical Depth: Comprehensive knowledge of cloud services (e.g., AWS, GCP, Azure) and experience in creating infrastructures optimized for AI workloads.
2. Programming Mastery: Proficient in Python, with demonstrable experience in crafting applications that interface with or support AI models and tasks. Knowledge of system and automation programming languages is expected.
3. DevOps and IAC Tools: Proficiency with CI/CD tools, Infrastructure as Code practices, and familiarity with DevOps paradigms tailored for AI operations.
4. Containerization & Orchestration: Knowledge of containers and orchestration tools suitable for deploying and scaling AI models.
5. Networking: Strong understanding of cloud networking fundamentals, with a focus on high-throughput and low-latency requirements typical of AI workloads.
6. Database Expertise: Practical experience with databases, especially in the context of large datasets typical in AI operations.
7. Monitoring Tools: Hands-on experience with tools to monitor both system health and AI model performance.
8. Soft Skills: Strong problem-solving abilities, good communication skills, and a collaborative spirit, especially in a multidisciplinary AI environment.
Required experience: 5+ years
Type of engagement: It is a long-term and full-time freelance agreement.
Hourly pay:
25 EUR / hour (for part-time, for the first month)
30 EUR / hour (for full-time)
possible to grow depending on the quality and delivery
Project period: ASAP, long-term, min 12 months extendable for another year. Part-time is possible for the first month, afterwards a full-time engagement is expected.
Methodologies: Agile / Scrum
Level of English: Good; Talking, Reading, and Writing
Place of work: remote home office, for the client in Germany
Apply on: office@volito.digital
