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• Handling critical incidents/escalations, reviewing incidents and tracking towards closure • Good experience in SIEM tools, event logging and event analysis • Good knowledge in enterprise security products like Firewalls, IPS, Web/content Filtering tools, Compliance tools • Team Management, performance monitoring and prepare reports on weekly, monthly basis and share to stakeholders as needed • Good knowledge about common security attacks, targeted attacks • Good experience in forensic analysis, Packet Analysis tools like Wireshar • Assisting, mentoring L2/L3 analysts and groom them to move to next level • Contribute to continue monitoring and improvement of security posture of the organization • Having experience of managing team of 25+ team members across multiple locations.
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• Primarily responsible for security event monitoring, management and response • Ensure incident identification, assessment, quantification, reporting, communication, mitigation and monitoring • Revise and develop processes to strengthen the current Security Operations Framework, Review policies and highlight the challenges in managing SLAs • Responsible for team & vendor management, overall use of resources and initiation of corrective action where required for Security Operations Center • Management, administration & maintenance of security devices under the purview of SOC which consists of state-of-the art technologies • Perform threat management, threat modeling, identify threat vectors and develop use cases for security monitoring • Responsible for integration of standard and non-standard logs in SIEM • Creation of reports, dashboards, metrics for SOC operations and presentation to Sr. Mgmt. • Co-ordination with stakeholders, build and maintain positive working relationships with them
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Shubham Vishwakarma
Full Stack Developer - Averlon
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Machine Learning (ML)
Amazon Web Services (AWS)MUST-HAVES:
- Machine Learning + Aws + (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) + Sage maker
- Notice period - 0 to 15 days only
- Hybrid work mode- 3 days office, 2 days at home
SKILLS: AWS, AWS CLOUD, AMAZON REDSHIFT, EKS
ADDITIONAL GUIDELINES:
- Interview process: - 2 Technical round + 1 Client round
- 3 days in office, Hybrid model.
CORE RESPONSIBILITIES:
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- Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.
- Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
- Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
- System Integration: Integrate models into existing systems and workflows.
- Model Deployment: Deploy models to production environments and monitor performance.
- Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
- Continuous Improvement: Identify areas for improvement in model performance and systems.
SKILLS:
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- Knowledge of model monitoring and performance evaluation.
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- AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
- AWS data: Redshift, Glue
- Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)
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Department, including onboarding of warehouses on Whrrl’s platform and
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Hike on current salary
Java
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Full Stack Developer - Averlon