Location
Bangalore | India
Job description
Sanas is revolutionizing the way we communicate with the world's first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard. Our initial deployment is laser-focused on elevating the standards of customer experience centers. Testimonials from our partners reveal staggering double-digit improvements in mission-critical KPIs, coupled with boosts in CSAT and NPS. More than just a tool, our technology champions a bias-free workspace. This not only fosters a positive work environment but has also been instrumental in reducing employee attrition and curbing training expenditures.
Sanas is a 70-strong team, established in 2020. In this short span, we've successfully secured over $50 million in funding. Our innovation have been supported by the industry's leading investors, including Insight Partners, Google Ventures, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you're not just adopting a product; you're investing in the future of communication.
Job Summary:
As a Junior DevOps Engineer at [Your Company Name], you will be a key contributor to our DevOps initiatives, primarily focusing on AWS with SageMaker and Dagster. Additionally, you will leverage your secondary skills in Kubernetes with Azure to enhance our infrastructure and deployment processes. This role offers an excellent opportunity to work with cutting-edge technologies and play a pivotal role in optimizing our development and deployment workflows
Key Responsibilities:
- Design, implement, and maintain CI/CD pipelines, with a primary focus on AWS services, especially SageMaker and Dagster
- Collaborate with development teams to automate and streamline deployment processes for machine learning models and data workflows
- Utilize AWS infrastructure as code tools (e.g., CloudFormation, Terraform) to manage and provision resources efficiently
- Implement and manage Kubernetes clusters on Azure for container orchestration
- Work closely with cross-functional teams to ensure scalability, reliability, and security of the infrastructure
- Troubleshoot and resolve issues in development, testing, and production environments
- Participate in on-call rotation and respond to incidents promptly to maintain system availability
- Stay abreast of industry best practices and emerging technologies related to AWS, SageMaker, Dagster, Kubernetes, and Azure
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field
- Primary skills in AWS, with hands-on experience in SageMaker and Dagster
- Secondary skills in Kubernetes, with experience in Azure Kubernetes Service (AKS).Proficiency in scripting languages such as Python, Bash, or PowerShell
- Experience with CI/CD tools like Jenkins, GitLab CI, or AWS CodePipeline
- Familiarity with containerization technologies (Docker) and container orchestration (Kubernetes).Understanding of infrastructure as code (IaC) concepts using tools like CloudFormation or Terraform
- Strong problem-solving skills and ability to troubleshoot complex issues
- Excellent communication and collaboration skills
Preferred Skills:
- Experience with version control systems, particularly Git
- Knowledge of machine learning concepts and workflows
- Familiarity with Azure DevOps services
- Understanding of security best practices in a DevOps environment
- Previous exposure to monitoring and logging tools such as Prometheus, Grafana, ELK stack, or similar
Job tags
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