Rapid Acceralation Partners
https://rapidautomation.ai/About
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NodeJS (Node.js)
React.js
Angular (2+)
AngularJS (1.x)
MongoDBPosition : Full Stack Developer
Location : Chennai
Experience : 4 – 6 Years
Job type : Permanent
Team: You will be part of an engineering team, developing software that enables customers to automate business processes with low-code/no-code. The product(s) that you will work on have Web Applications, Web Services, AI components/services, Desktop and Browser automation
components, Data Pipelines, Analytics, Frameworks for development/testing/CICD and more.
Responsibilities: Full Stack Engineer, i.e.
• Work on any/all layers of existing or new products, developing end to end features
• Build generic or custom solutions for PoCs
• Package/deploy/support/maintain the product in production and dev/test environments
Skills - Must have:
• Full Stack Development
• React
• Node.js
• TypeScript
• MongoDB
Skills – Good to have:
• Docker
• Node-RED
• DevOps - CI/CD
• Cloud deployment, architecture and technologies
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
NodeJS (Node.js)React.jsAngular (2+)AngularJS (1.x)MongoDBMust-have:
-Overall 3 - 5 years of experience
-At least 2+ years Front End
-At least 2+ years Backend development
-Node.js
-Any front-end technology (React.js is not mandatory)
-Any NoSQL (non-relational) database like MongoDB, Cassandra etc.
-Must have worked mostly on Web Applications
-Docker
-Either Competitive Programming Experience (leet code, codechef, hackerrank etc.) OR personal project submissions on github etc.
Optional / Good-To-Have:
-Aws / Azure / GCP experience
-DevOps
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Data Science
Machine Learning (ML)Roles & Responsibilities:
-Adopt novel and breakthrough Deep Learning/Machine Learning technology to fully solve real world problems for different industries. -Develop prototypes of machine learning models based on existing research papers.
-Utilize published/existing models to meet business requirements. Tweak existing implementations to improve efficiencies and adapt for use-case variations.
-Optimize machine learning model training and inference time. -Work closely with development and QA teams in transitioning prototypes to commercial products
-Independently work end-to-end from data collection, preparation/annotation to validation of outcomes.
-Define and develop ML infrastructure to improve efficiency of ML development workflows.
Must Have:
- Experience in productizing and deployment of ML solutions.
- AI/ML expertise areas: Computer Vision with Deep Learning. Experience with object detection, classification, recognition; document layout and understanding tasks, OCR/ICR
. - Thorough understanding of full ML pipeline, starting from data collection to model building to inference.
- Experience with Python, OpenCV and at least a few framework/libraries (TensorFlow / Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)
- Years with relevant experience:
5+ -Experience or Knowledge in ML OPS.
Good to Have: NLP: Text classification, entity extraction, content summarization. AWS, Docker.
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