Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.
An automated data orchestration and pipeline management platform.
An AI-powered, enterprise-ready Gen AI platform for internal teams.
Parsing engine and interactive mapper.
Precision parsing, mapping, transformation & health data analytics.
Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.
Custom, integrated predictive layer.
Automated data movement for faster time-to-insights.
Consolidated data for improved accessibility.
Structured data for reporting, analytics and model training.
Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.
Explore how businesses leveraged our data solutions to their advantage.
Keep up with the latest trends to scale faster and outwit competition.
Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.
We are a bold team supporting bold leaders like you ready to adopt and migrate to new technologies.
Discover the essence of our tech beliefs and explore the possibilities they offer your business.
Unlock your business potential by leveraging Gen AI and capitalizing on rich datasets.
Lead your business to new heights and scale effortlessly with expert guidance along the entire customer journey.
We are looking for an enthusiastic and motivated Machine Learning Engineer to assist in building and deploying machine learning models and data systems. This entry-level role is ideal for candidates eager to apply their technical skills to real-world problems and grow as part of a collaborative team.
Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field
Technical Skills:
Experience: 0-1 years of experience in data engineering or related fields.
Soft Skills:
Preferred Skills/Qualifications
Education: Bachelor’s degree in Computer Science, Information Technology, or related field.
Technical Skills:
Experience: 0-1 year
Key Performance Indicators:
Hear inspiring stories about their professional journey and
life at this open, inclusive workspace.