Lead Machine Learning Research Engineer₹25L – ₹35L • No equity
Vernacular.ai is a Series A funded startup, we are an AI-First SaaS business that is driven with a mission to become the leading voice automation/AI platform in the world. Our team has extensive experience in the AI/automation space and through constant reiteration and hard work, we have successfully built our state of the art AI-based voice automation platform - VIVA. Currently, we have deployed our product in enterprise contact centers and are keen to deliver high value. We are a young, entrepreneurial, energetic team that's looking to disrupt the voice domain.
We are looking for ML Research Engineering Lead to work on and oversee works 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.
You will be a critical member of our Machine Learning team working on designing, developing and augmenting ML models and algorithms. A regular roster for the role looks like the following:
- Design, evaluate and oversee implementations of our Machine Learning systems.
- Perform experiments and statistical analyses to draw conclusions and take modeling decisions.
- Understand the situatedness of tasks and adapt existing techniques for the problem.
- Take part in regular research reviews and discussions. Mentor other team members. Create and layout internal roadmaps for the ML team.
- Architect and review 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.
- 2+ years of industrial or academic experience.
- 2+ years of experience in Machine Learning, preferably in NLP/Speech.
- 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.
- 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.
Work-from-home friendly, flexible work hours.
As long as you stick to the work/ deliverables. That is all matters.
Snacks, beverages and more
Everyday Snacks Beverages once in a while Team Outings Game Nights Movie/ Sports Marathons
Vernacular.ai at a glance
Vernacular.ai focuses on Enterprise Software, Artificial Intelligence, and Natural Language Processing. Their company has offices in Bengaluru. They have a mid-size team that's between 51-200 employees.