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.

About the Role:

Sanas is looking for an experienced Cloud Architect with a strong background in software engineering and managing complex compute and security requirements. In this role you will be responsible for managing the cloud resources used by the ML engineering and Data science teams at Sanas. You will also be developing tools to use and monitor the cloud infrastructure. You will also be collaborating with other teams to ensure compatibility and standardization.

Here's what you’ll be doing:

• Design and maintain Sanas’s cloud infrastructure for ETL, agile development, and scientific experimentation
• Manage resources and permissions to keep in line with company wide infosec requirements
• Manage resources to maximize the cost benefit
• Develop and maintain tools for ML engineers and Data Scientists to utilize cloud resources
• Develop and maintain dashboards and other monitoring tools for performance and costing
• Advising management about technical impact on business decisions
• Generate documentation for ML engineers and data scientists to maximize the use of cloud architecture
• Debug and troubleshoot cloud related issues
  
  
  

Must have:

• Proven experience in sagemaker and dagster
• Practical and theoretical knowledge of infrastructure as code
• Bachelor's or Master's Degree in Computer Science, Engineering, or a related field
• Proven experience in software engineering, preferably in Python
• Proven experience with cloud providers such as AWS, GCP, or Azure
• Proven experience with IAM
• Proven experience with reporting tools like Grafana
  
  
  

Preferred qualifications:

• Hands-on experience with deep learning tools such as Kubeflow, Dagster, and Weights and Biases
• Experience with large-scale ML systems, cloud infrastructure, and IT
• Experience with DevOps practices such as containerization and CI/CD
• Experience with data engineering, data warehousing, and data processing technologies