Passionate about Scaling Hardware Deployment of AI on Cloud ?
We are building the first NO-CODE AI PLATFORM for the AEC industry, with the 3rd generation Explainable AI, that allows users to create complex use cases with zero coding at the frontend and neuro-symbolic AI under the hood.
We are looking for a Deep Learning Deployment Engineer (Cloud) to join our Bengaluru office.
You will be part of our product development team and will work closely with other AI Engineers to optimize and deploy AI models on clouds and servers at scale.
Optimize AI models (compression, quantization, etc) for deployment on cloud
Create dockerized versions of the optimized models
Deploying the dockerized models on scalable distributed infrastructure
Lifecycle management of the deployed models
The technology will scale in public/private cloud across a rapidly increasing number of customers in multiple geographies, while processing and rendering large amount of based data points.
B Tech / M Tech in Computer Engineering from a top tier university
5+ years of hands-on experience with Machine Learning & Deep Learning models and their deployment to production on private, hybrid and public clouds
Automated creation of dockerized versions of the software
Knowledge of AI model optimization techniques (compression, quantization, etc)
Experience in designing, building, and running scalabale distributed infrastructure
Experienced in Python and Bash scripting
Certifications in the field of cloud technologies and solutions like GCP, AWS, AZURE, etc.
Design and implementation of concepts/architecture for private, hybrid and multi-cloud scenarios
Experience in relational cloud based database technologies and proficiency in SQL
Analyze production workloads and develop strategies to run database with scale and efficiency
Experience in scaling-up and scaling-out fragmented/distributed databases
Experience with all aspects of database security both at infrastructure and application level
Knowledge or experience of working basic OS and Networking database related issues.
Configuration Management of varied types of deployment environments, specifying compute and memory requirements
Monitoring and Analytics such as AWS CloudWatch, BigPanda, GoogleStackDriver
Extensive experience in productionization of AI models
Experience with Container-Orchestration/Deployment tools such as Kubernetes and/or Docker
Knowledge in using popular MLOps frameworks like Kubeflow, MLFlow, and DataRobot
Excellent communication skills in English
Competitive salary (INR 20L - 28L per annum) depending on the experience
The $12 Trillion construction industry is one of the “least digitalized” industries and has a major productivity problem. We aim to empower the construction industry with No-Code AI to revolutionize knowledge management and help close the productivity gap.
We are building the first of its kind NO-CODE AI PLATFORM for the construction industry, which makes it easy even for non-tech users to configure and scale AI-powered applications for a variety of use cases, without writing a single line of code. Use cases would be far-reaching, from enhanced jobsites visibility to delivering actionable insights for decision support and, (in future), enabling autonomy in machinery & robotics.
The platform, built with advanced 3rd generation "Explainable AI (XAI)", analyzes and interprets sensor, transactional and historical project data, and different forms of knowledge, to generate descriptive and prescriptive insights.
**Zero coding at the frontend and neuro-symbolic AI under the hood.**