Ccube prides itself on being an employer of choice, consistently attracting exceptional and talented individuals thanks to its unwavering focus on cutting-edge technologies and exclusive data driven projects.
Ccube is a rapidly growing digital technology service provider and a preferred partner for numerous Fortune 500 companies aiming to leverage disruption for competitive advantage through innovative digital strategies. Ccube leverages its proficiency in transforming customer experiences, data analytics, artificial intelligence, platform and product engineering, cloud infrastructure, and security to assist clients in rapid innovation for expansion, development of digital products, establishment of service platforms, and enhancement of data-driven performance.
Title - AI/ML Engineer
Multiple Locations - Charlotte, NC ( Primary ) / Concord , CA ( Secondary )
Key Responsibilities:
Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-
prem and cloud platforms.
Responsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI,
Azure ML)
Collaborating with Data scientist to optimize the scoring pipeline.
Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-
prem platform and cloud platform.
Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
Build and Deploy capabilities for data pipeline deployment standardization and model
consumption by multiple LOBs.
Collaborate with product owners, devOps team, data scientists, support teams to define and
drive end to end model scoring pipelines.
Participate in day-to-day standups for platform capability build.
Provide SME guidance for data science teams on software engineering principles, model
deployments, platform capabilities.
Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB
Technology using standardized platform processes and capabilities.
Support Production Issues partnering with production support.
Key Requirements:
5+ years of Python experience
5+ years of big data experience needed (Big Query, Hadoop)
3 years of experience in AIML area (MLOps)
2+ years of experience in developing APIs using Python/FastAPI.
1+ year of Document AI, Agent Builder/GCP search/conversation / Dialogflow – Nice to have
Good to have 1+year of experience in LLM, Generative AI (developing capabilities or dev/ops)
Good to have Experience in developing of API on GCP/Azure/API Gateways
Good to have 1+year of experience in Vector Database, Model Development would be added
benefit.
Education:
Bachelor’s or master’s degree in computer science, data science, or related discipline
Professional certificates (e.g., Data Science, Data Analyst) a plus
Actual compensation is influenced by years of experience, specialized skill sets, and unique qualifications
Ccube provides various benefits such as subsidized medical, dental, vision Insurance
Top Skills
What We Do
Driving Innovation through Advanced Data and AI Services.
We offer next-level data and AI services to help you transform your data into actionable insights for a competitive edge.
To augment your teams, we offer full-time/contract resources & consulting, design and development services for turnkey projects in the following areas:
01 DATA MODERNIZATION
Define Cloud strategy, architecture & roadmap
Identify current landscape & catalog data sources
Data warehouse design & setup
Develop data governance & data quality framework
Implement data management technologies
Build data analytics capabilities
Inculcate data driven culture
A future-ready framework to serve all business use cases
02 DATA INTEGRATION & CLOUD MIGRATION
Design & develop
Optimized data models and data pipelines
ETL/ELT workloads & monitoring
Processes that scale up and down without performance problems
Automate data migration between upstream/downstream (on-prem) systems and Cloud
03 DATA ANALYTICS & AI
Data analytics consulting – use-case exploration and building analytics roadmap
Data preparation and creating a single version of truth
Dashboard & report development
AI/ML model selection and development
AI/ML model tuning and validation
AI/ML model scaling, integration and deployment
