Artificial Intelligence and Machine Learning Engineer

AI/ML Engineer

Mandatory Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 7 to 9 years of practical experience. 
• Proven experience as a DevOps Engineer or Software Engineer in an agile, cloud-based environment. 
• Hands-on experience with cloud platforms (AWS, Azure, GCP) - AI/ML services experience preferred. 
• Proficient in infrastructure automation tools such as Terraform, Helm Charts, Ansible, etc. 
• Strong understanding of DevOps practices/tools, including CI/CD, Pipelines, GitHub Actions, and Infrastructure as Code. 
• Basic scripting knowledge in Python, able to write automation scripts in Python and Groovy DSL. 
• Experienced in managing the delivery of high-availability infrastructure to support mission-critical systems and services. 
• Experience with source version control tools like Azure Repos and GitHub. 
• Experience with containerization (Kubernetes, Docker) and orchestration. 
• Strong knowledge of networking concepts (TCP/IP, VNet/Subnet, DNS, Load Balancers, Application Gateway, etc.) and security practices (VPN, Firewalls, encryption).
• Familiarity with databases and caching mechanisms used in our stack, such as PostgreSQL and Redis. 
• Experience in handling complex IT infrastructure solution design and implementation. 
• Excellent communication and interpersonal skills, effective problem-solving skills, logical thinking ability, and strong commitment to professional and client service excellence. 
• Excellent teamwork skills and the ability to direct efforts of cross-functional teams for a collaborative proposition. — Strong synthesis and analytical skills. 

Experience working in a consulting environment is an added advantage

 

• Design, implement, and maintain scalable and secure cloud infrastructure to support applications built on Django, Python, Node.js, and React.js
• Demonstrate advanced troubleshooting expertise in Azure and GCP cloud environments
• Possess in-depth knowledge of Azure and GCP troubleshooting methodologies, including:
  • Advanced diagnostic techniques
  • Performance analysis
  • Root cause investigation
  • Complex system issue resolution
• Demonstrate good knowledge of Helm and Kubernetes
• Maintain a solid understanding of Azure DevOps (ADO) tools, including boards, repos, pipelines, and artifacts.
• Collaborate with development teams to streamline CI/CD pipelines, enabling seamless code deployment and faster delivery cycles.
• Conduct comprehensive monitoring (Application Insights, Log Analytics, Grafana) and advanced troubleshooting of application performance and system reliability.
• Identify and resolve complex infrastructure and cloud-related issues across Azure and GCP platforms.
• Utilize Python and Groovy for advanced troubleshooting scripts and automation tasks.
• Develop and implement proactive monitoring and diagnostic strategies for cloud infrastructure.
• Work closely with security teams to ensure tool compliance and rapid issue resolution.
• Reduce system toil through intelligent troubleshooting and automation approaches.

• Bachelor's degree in Computer Science, Engineering, or a related field
• 3+ years of experience in DevOps role
• Excellent problem-solving skills

Experience Level

Senior Level