Senior AI Infrastructure Engineer
Office Beacon LLC
Date: 5 hours ago
City: Vadodara, Gujarat
Salary:
₹3,500,000
-
₹4,000,000
per year
Contract type: Full time
Remote
Description
We are seeking a highly skilled and experienced Senior AI Infrastructure Engineer to join our innovative Information Technology department. This role is pivotal in designing, building, and maintaining the robust and scalable infrastructure essential for our cutting-edge Artificial Intelligence and Machine Learning initiatives. The successful candidate will play a critical role in enabling our data scientists and AI researchers to efficiently develop, train, and deploy advanced models, driving significant impact across our organization. This position offers a unique opportunity to contribute to the foundational architecture that underpins our AI strategies. You will work with a diverse set of technologies, focusing on creating a seamless and performant environment for AI model development, deployment, and management. We are looking for an individual who thrives in a fast-paced environment, possesses deep technical expertise in distributed systems and cloud platforms, and is passionate about solving complex infrastructure challenges to unlock the full potential of AI.
Requirements
Demonstrated expertise in designing and implementing large-scale distributed systems and cloud-native architectures. Profound understanding of machine learning lifecycle and the infrastructure requirements for each stage. Strong command of at least one major cloud platform (AWS, Azure, GCP) with emphasis on AI/ML services. Experience with containerization (Docker) and orchestration technologies (Kubernetes). Proficiency in scripting and automation using languages such as Python, Bash, or Go. Ability to diagnose and resolve complex technical issues in a multi-faceted infrastructure environment.
Responsibilities
Design, implement, and maintain highly available and scalable infrastructure for AI/ML workloads, including compute, storage, and networking components. Develop and manage MLOps pipelines for automated model training, evaluation, versioning, deployment, and monitoring. Optimize cloud resource utilization for AI applications, focusing on cost-efficiency, performance, and reliability. Evaluate, integrate, and manage various AI/ML tools and platforms to enhance the overall AI development ecosystem. Collaborate closely with data scientists, ML engineers, and other IT teams to understand requirements and provide expert infrastructure solutions. Establish and enforce best practices for security, data governance, and compliance within the AI infrastructure.
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Extensive experience in an infrastructure engineering role, with a significant focus on AI/ML platforms. Proven track record of building and managing robust, scalable, and secure infrastructure solutions.
Core Focus Areas
AI Platform Architecture & Design Scalable ML Workflow Automation Cloud Resource Optimization for AI/ML Observability and Performance of AI Systems
Schedule
19:30 – 05:30 IST — PST
We are seeking a highly skilled and experienced Senior AI Infrastructure Engineer to join our innovative Information Technology department. This role is pivotal in designing, building, and maintaining the robust and scalable infrastructure essential for our cutting-edge Artificial Intelligence and Machine Learning initiatives. The successful candidate will play a critical role in enabling our data scientists and AI researchers to efficiently develop, train, and deploy advanced models, driving significant impact across our organization. This position offers a unique opportunity to contribute to the foundational architecture that underpins our AI strategies. You will work with a diverse set of technologies, focusing on creating a seamless and performant environment for AI model development, deployment, and management. We are looking for an individual who thrives in a fast-paced environment, possesses deep technical expertise in distributed systems and cloud platforms, and is passionate about solving complex infrastructure challenges to unlock the full potential of AI.
Requirements
Demonstrated expertise in designing and implementing large-scale distributed systems and cloud-native architectures. Profound understanding of machine learning lifecycle and the infrastructure requirements for each stage. Strong command of at least one major cloud platform (AWS, Azure, GCP) with emphasis on AI/ML services. Experience with containerization (Docker) and orchestration technologies (Kubernetes). Proficiency in scripting and automation using languages such as Python, Bash, or Go. Ability to diagnose and resolve complex technical issues in a multi-faceted infrastructure environment.
Responsibilities
Design, implement, and maintain highly available and scalable infrastructure for AI/ML workloads, including compute, storage, and networking components. Develop and manage MLOps pipelines for automated model training, evaluation, versioning, deployment, and monitoring. Optimize cloud resource utilization for AI applications, focusing on cost-efficiency, performance, and reliability. Evaluate, integrate, and manage various AI/ML tools and platforms to enhance the overall AI development ecosystem. Collaborate closely with data scientists, ML engineers, and other IT teams to understand requirements and provide expert infrastructure solutions. Establish and enforce best practices for security, data governance, and compliance within the AI infrastructure.
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Extensive experience in an infrastructure engineering role, with a significant focus on AI/ML platforms. Proven track record of building and managing robust, scalable, and secure infrastructure solutions.
Core Focus Areas
AI Platform Architecture & Design Scalable ML Workflow Automation Cloud Resource Optimization for AI/ML Observability and Performance of AI Systems
Schedule
19:30 – 05:30 IST — PST
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