Conversational AI platform built at Haptik has been powering chatbots since 2013, way before chatbots were cool. We are currently looking to grow our Machine Learning team to strengthen and expand multiple research projects in the domain of information retrieval, intent and entity extraction from complex dialogues, personalising chatbots with emotions and personality. As Senior Architect, you should be willing to deep dive into Haptik’s machine learning pipeline which has exchanged more than 2 billion messages over more than 300 enterprise bots. This position directly works with leadership team and Founders to align Haptik’s technology stack with the vision of the company.
Own the performance of Haptik’s machine learning pipeline which is primarily measured in terms of response time of the bots built using Haptik’s conversational AI platform.
Setup training and testing performance benchmarks for machine learning models being developed at Haptik
Setup appropriate communication protocol and optimise architecture of existing ML micro-services
Optimise resources used by ML models in production and during training process
Work with research team to foresee data requirements and build a pipeline for generation and management of training data for future projects
Own logging and reporting of Haptik’s end to end message pipeline
Continuously track architectural development across evolving ML frameworks (TensorFlow, PyTorch, Scikit, etc) and make sure research team uses right technology
5+ years of industry experience and familiarity with data flow across end to end lifecycle of ML project including data ingestion, indexing/ mining, transformation and validation
Hands on experience in building distributed system including real time streaming and batch data processing
Proven and successful experience in handling large scale text datasets
Proficient at multiple programming languages relevant to such systems (Python, Java, C++)
Strong fundamentals and experience working with SQL, NoSQL and graph Database
Experience with designing service-oriented architecture and leveraging various datastore technologies (MySQL, Redis, Elasticsearch, etc.)
Experience with cloud computing platforms such as AWS, GCP or Azure