Vernacular.ai
https://vernacular.aiAbout
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Machine Learning (ML)
Deep LearningAbout us
Skit (previously known as http://vernacular.ai/" target="_blank">Vernacular.ai) is an AI-first SaaS voice automation company. Its suite of speech and language solutions enable enterprises to automate their contact centre operations. With over 10 million hours of training data, its product - Vernacular Intelligent Voice Assistant (VIVA) can currently respond in 16+ languages, covering over 160+ dialects and replicating human-like conversations.
Skit currently serves a variety of enterprise clients across diverse sectors such as BFSI, F&B, Hospitality, Consumer Electronics and Travel & Tourism, including prominent clients like Axis Bank, Hathway, Porter and Barbeque Nation. It has been featured as one of the top-notch start-ups in the Cisco Launchpad’s Cohort 6 and is a part of the World Economic Forum’s Global Innovators Community. It has has also been listed in Forbes 30 Under 30 Asia start-ups 2021 for its remarkable industry innovation.
We are looking for ML Research Engineers to work on the following problems:
- Spoken Language Understanding and Dialog Management.
- Language semantics, parsing, and modeling across multiple languages.
- Speech Recognition, Speech Analytics and Voice Processing across multiple languages.
- Response Generation and Speech Synthesis.
- Active Learning, Monitoring and Observability mechanisms for deployments.
Responsibilities
- Design, build and evaluate Machine Learning solutions.
- Perform experiments and statistical analyses to draw conclusions and take modeling decisions.
- Study, implement and extend state of the art systems.
- Take part in regular research reviews and discussions.
- Build, maintain and extend our open source solutions in the domain.
- Write well-crafted programs at all levels of the system. This includes the data pipelines, experiment prototypes, fast and scalable deployment models, and evaluation, visualization and monitoring systems.
Requirements
- Practical Machine Learning experience as demonstrated by earlier works.
- Knowledge of and ability to use tools from theoretical and practical aspects of computer science. This includes, but is not limited to, probability, statistics, learning theory, algorithms, software architecture, programming languages, etc.
- Good programming skills and ability to work with programs at all levels of a finished Machine Learning product. We prefer language agnosticism since that exemplifies this point.
- Git portfolios and blogs are helpful as they let us better evaluate your work.
- What information we collect during our application and recruitment process and why we collect it;
- How we use that information; and
- How to access and update that information.
This policy covers the information you share with Skit (Cyllid Technologies Pvt. Ltd.) during the application or recruitment process including:
- Your name, address, email address, telephone number and other contact information;
- Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
- Information from interviews and phone-screenings you may have, if any;
- Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
- Details of how you heard about the position you are applying for;
- Reference information and/or information received from background checks (where applicable), including information provided by third parties;
- Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
- Information related to any assessment you may take as part of the interview screening process.
Your information will be used by Skit for the purposes of carrying out its application and recruitment process which includes:
- Assessing your skills, qualifications and interests against our career opportunities;
- Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
- Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
- Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
- Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
- Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Python
Django
FlaskAbout us
Skit (previously known as http://vernacular.ai/" target="_blank">Vernacular.ai) is an AI-first SaaS voice automation company. Its suite of speech and language solutions enable enterprises to automate their contact centre operations. With over 10 million hours of training data, its product - Vernacular Intelligent Voice Assistant (VIVA) can currently respond in 16+ languages, covering over 160+ dialects and replicating human-like conversations.
Skit currently serves a variety of enterprise clients across diverse sectors such as BFSI, F&B, Hospitality, Consumer Electronics and Travel & Tourism, including prominent clients like Axis Bank, Hathway, Porter and Barbeque Nation. It has been featured as one of the top-notch start-ups in the Cisco Launchpad’s Cohort 6 and is a part of the World Economic Forum’s Global Innovators Community. It has also been listed in Forbes 30 Under 30 Asia start-ups 2021 for its remarkable industry innovation.
We have an opening for a Software Engineer(Solution) role which you might be interested in.
Responsibilities of your role:
- You will be coordinating our enterprise account-specific teams called squads, consisting of members from engineering, machine-learning, and conversation-design teams.
There are five working groups in the organization, (i) Business (ii) Research (iii) Solutions (iv) Product, and (v) Operations, where you will be joining the Solutions working group.
- You will be collaborating with the sales team to design an appropriate solution to the customer's problems and help them showcase the value in the product.
- You will be collaborating with the operations team to ensure we are not compromising on our quality standards.
- You will also be co-working with the product working group to help them improve the overall platform and to prioritize the high-impact initiatives in the roadmap.
Work you will be doing:
- You will be building bespoke voicebots for enterprise clients using internal tools.
- You're expected to help build the Solutions stack whose goal it is to reduce the amount of effort put into building our voicebots.
- You will be involved in analyzing client calls where you're expected to use either data pipelines or SQL to get insights into caller behavior.
Technical Requirements
Mandatory Requirements:
- Professional experience of at least 1 year.
- Has experience with integrating or building HTTP APIs
- Has hands-on experience of working with Python
- Good communicator
Optional Requirements:
- Has experience working in any of Django Rest Framework, Redis, Celery
Technical Stack
Skit uses a microservices architecture where we employ both HTTP and GRPC to communicate between our services.
We don't expect you to have worked on all of it. We're looking for Python programmers who are ready to pick up the rest of the tech stack on the job.
Languages:
- Python
- Golang
Frameworks:
- Python:
- Django Rest Framework
- Celery
- Golang:
- Gorm
- GorillaMux
Tools/Orchestration/VCS:
- Docker
- Kubernetes
- Argo Workflows
- Gitlab
- Github
- What information we collect during our application and recruitment process and why we collect it;
- How we use that information; and
- How to access and update that information.
This policy covers the information you share with Skit (Cyllid Technologies Pvt. Ltd.) during the application or recruitment process including:
- Your name, address, email address, telephone number and other contact information;
- Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
- Information from interviews and phone-screenings you may have, if any;
- Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
- Details of how you heard about the position you are applying for;
- Reference information and/or information received from background checks (where applicable), including information provided by third parties;
- Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
- Information related to any assessment you may take as part of the interview screening process.
Your information will be used by Skit for the purposes of carrying out its application and recruitment process which includes:
- Assessing your skills, qualifications and interests against our career opportunities;
- Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
- Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
- Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
- Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
- Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.
We collect and process some or all of the following types of information from you:
- Information that you provide when you apply for a role. This includes information provided through an online job site, via email, in person at interviews and/or by any other method.
- In particular, We process personal details such as name, email address, address, telephone number, date of birth, qualifications, experience, information relating to your employment history, skills experience that you provide to Us, as well as your video in case you conduct your interview using the Video Interview feature.
- If you contact Us, We may keep a record of that correspondence.
- A record of your progress through any hiring process that we may conduct.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Docker
Kubernetes
Amazon Web Services (AWS)- 2+ years of demonstrable experience leading site reliability and performance in large-scale, high-traffic environments
- 2+ years of hands-on experience as a DevOps engineer
- Strong leadership, communication and interpersonal skills geared to getting things done
- Developing themselves and the talent within their charge – fostering and creating opportunity for the team
- Strong understanding of SRE concepts and the DevOps culture. Set the direction and strategy for your team, and help shape the overall SRE program for the company
- Be able to lead complicated technical issues and communicating status updates/RCA with management and customers.
- Own site stability, performance, capacity planning, DevOps recruitment.
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We started with a simple question: w̲h̲a̲t̲ i̲f̲ y̲o̲u̲r̲ t̲e̲a̲m̲ c̲o̲u̲l̲d̲ f̲o̲c̲u̲s̲ o̲n̲ w̲h̲a̲t̲ t̲h̲e̲y̲ l̲o̲v̲e̲ m̲o̲s̲t̲?̲
𝐎𝐮𝐫 𝐚𝐧𝐬𝐰𝐞𝐫:
AI voice employees that handle the work nobody wants to do. Customer calls at 11 PM. Follow-ups that slip through the cracks. Onboarding that takes forever. These aren't just tasks—they're the things that keep great people from doing great work.
𝐖𝐡𝐚𝐭 𝐰𝐞'𝐯𝐞 𝐥𝐞𝐚𝐫𝐧𝐞𝐝:
The best technology feels invisible. Our AI employees don't feel like software—they feel like that reliable teammate who just gets things done. No hand-holding, just consistent results that make everyone's day better.
𝐇𝐨𝐰 𝐰𝐞 𝐭𝐡𝐢𝐧𝐤 𝐚𝐛𝐨𝐮𝐭 𝐢𝐭:
This isn't about replacing anyone. It's about giving your team superpowers. When AI handles the repetitive conversations, your people can focus on solving problems, building relationships, and creating things that matter.
𝐖𝐡𝐚𝐭 𝐝𝐫𝐢𝐯𝐞𝐬 𝐮𝐬:
Every business has incredible people doing mundane work. We think that's backwards. So we built AI employees that free up human potential—one conversation at a time.
We're not trying to change the world overnight. We're just making tomorrow a little better than today, for teams who believe work should be meaningful.
Ready to give your team superpowers?
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