Job Role : AIML OPS Engineer
Salary : Rs 10,25,000 per year.
Location : Bengaluru, Karnataka
Company : Dell
Qualifications : Graduate
Experience : 7- 12 years
ABOUT DELL
Dell Technologies, based by using Michael Dell in 1984, has evolved into one of the world’s biggest technology infrastructure agencies. Known to start with for its modern technique to direct sales of private computer systems, Dell has various right into a comprehensive range of IT answers and services. The organization’s product portfolio spans from laptops, desktops, and servers to storage systems, networking system, and peripherals.
Dell’s acquisition of EMC Corporation in 2016 in addition reinforced its role in corporation storage and cloud computing. The organization serves a wide spectrum of clients, including individuals, small businesses, massive establishments, and public area customers globally.
In addition to hardware, Dell gives strong software program and protection answers through subsidiaries like VMware and RSA Security. Its commitment to sustainability is evident in tasks geared toward reducing environmental impact and selling ethical practices across its supply chain. Dell continues to innovate, that specialize in emerging technology including AI, IoT, and side computing, ensuring it remains at the leading edge of the digital transformation era.
Job Description
As an AIML Ops Engineer, you could orchestrate AI/ML fashions’ deployment, making sure strong scalability, overall performance, and reliability. Your characteristic includes taking part with facts scientists and software software engineers to integrate fashions into production structures efficiently. You’ll manage infrastructure provisioning, tracking, and optimization to uphold issuer-diploma targets. Additionally, you may put in force CI/CD pipelines for seamless updates and conduct root cause evaluation for incidents. Your data in cloud platforms, containerization (e.G., Docker, Kubernetes), and scripting languages (Python, Bash) might be pivotal. Strong hassle-solving skills and a proactive method to evolving generation are critical for fulfillment in this role.
Key Responsibilities for a AIML OPS Engineer:
- AI/ML Model Deployment: Deploy and control AI/ML models in production environments, ensuring seamless integration with present structures and packages.
- Scalability and Performance: Orchestrate the scaling of AI/ML solutions to deal with varying workloads efficaciously. Optimize average overall performance to meet issuer-stage agreements (SLAs) and man or woman expectations.
- Reliability and Availability: Implement strategies for excessive availability and reliability of AI/ML offerings. Monitor structures closely to proactively become aware of and cope with functionality troubles.
- Infrastructure Management: Manage cloud infrastructure assets (AWS, GCP, Azure) to manual AI/ML workloads. Utilize containerization era like Docker and orchestration system which incorporates Kubernetes for green beneficial aid allocation and management.
- Automation and CI/CD: Develop and keep CI/CD pipelines for automatic finding out, deployment, and updates of AI/ML models. Ensure clean integration and shipping of recent features and improvements.
- Monitoring and Alerting: Establish monitoring frameworks to song AI/ML model ordinary performance, infrastructure utilization, and machine health. Set up alerting mechanisms to right away reply to anomalies and incidents.
- Security and Compliance: Implement security satisfactory practices and compliance measures for AI/ML deployments. Ensure information privacy, integrity, and regulatory necessities are met.(AIML OPS Engineer)
- Collaboration with Teams: Work intently with records scientists, software engineers, and move-practical groups to recognize requirements, integrate models into packages, and troubleshoot problems collaboratively.
- Documentation and Reporting: Maintain documentation for deployment strategies, configurations, and troubleshooting steps. Generate reports on system ordinary overall performance, incidents, and improvements.
- Continuous Learning: Stay up to date with the ultra-current trends and improvements in AI/ML operations, cloud technology, and DevOps practices. Apply new realize- how to beautify operational efficiencies and abilities.
Key Skills for a AIML OPS Engineer:
- AI/ML Operations: Solid expertise of gadget studying fashions and frameworks (e.G., TensorFlow, PyTorch). Experience in deploying and handling AI/ML fashions in production environments.
- Cloud Platforms: Proficiency in cloud systems such as AWS, GCP, or Azure. Ability to provision, configure, and optimize cloud infrastructure to assist AI/ML workloads.
- Containerization and Orchestration: Hands-on revel in with Docker and Kubernetes for containerization, orchestration, and microservices deployment. Familiarity with box manipulate equipment like Docker Swarm or Kubernetes operators.
- Programming and Scripting: Strong programming capabilities in languages which include Python, Bash, or similar. Ability to write scripts for automation, monitoring, and deployment obligations.(AIML OPS Engineer)
- CI/CD Pipelines: Experience in putting in and handling CI/CD pipelines the usage of device like Jenkins, GitLab CI/CD, or CircleCI. Knowledge of model manage structures (e.G., Git) for code manipulate.
- Monitoring and Logging: Proficiency with tracking equipment such as Prometheus, Grafana, ELK stack (Elasticsearch, Logstash, Kibana). Ability to set up metrics, dashboards, and logging for AI/ML structures.
- Adaptability and Learning Agility: Willingness to study new generation and adapt to evolving environments. Ability to brief hold close and practice new concepts in AI/ML operations and DevOps practices.
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