Model Integration Trainee Job at Openkyber, Virginia

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  • Openkyber
  • Virginia

Job Description

Job Description: Model Integration Trainee Overview

We are seeking a motivated Model Integration Trainee to support the development, integration, and testing of AI/ML models, data workflows, and enterprise automation pipelines. This role is ideal for freshers or early-career professionals interested in AI integration, RAG workflows, APIs, and data engineering .
You will work closely with senior engineers and architects to learn how AI-driven systems integrate with platforms like ServiceNow, Databricks, and vector databases .

Key Responsibilities AI & Model Workflow Support
  • Assist in building basic components of AI workflows such as data parsing, classification, and routing logic .

  • Support retrieval-based systems including vector search, embeddings, and RAG pipelines .

  • Perform model testing, output validation, and logic flow verification.

System Integration & API Support
  • Learn and contribute to integrating AI models with enterprise systems using REST APIs .

  • Support tasks such as sending API test calls, validating system responses, and checking logs.

  • Document integration steps and assist in maintaining workflow diagrams.

Databricks & Data Pipeline Assistance
  • Assist in managing datasets, Delta tables, and workspace organization inside Databricks .

  • Support model deployment tasks by preparing environments, files, and test inputs.

  • Monitor pipeline performance and conduct basic data quality checks.

Documentation & Collaboration
  • Create and maintain documentation for workflows, test cases, and integration activities.

  • Participate in team meetings, take notes, and help with task tracking.

  • Follow coding and documentation standards for clean, maintainable work.

Ideal Candidate Profile
  • Strong interest in AI model integration, automation, and data workflows .

  • Basic knowledge of Python or willingness to learn quickly.

  • Curiosity about APIs, NLP, vector databases, and LLM-based systems.

  • Strong analytical skills and a problem-solving mindset.

  • Good communication skills and eagerness to learn from senior engineers.

Preferred (Not Mandatory) Skills
  • Understanding of NLP or LLM fundamentals.

  • Basic familiarity with REST APIs.

  • Exposure to Databricks, cloud platforms, or vector databases.

  • Awareness of RAG concepts and embeddings.

  • Experience with Python libraries like NumPy, Pandas, or LangChain.

What You Will Learn
  • Building and integrating real-world RAG and AI systems .

  • How AI agents interact with enterprise tools (e.g., ServiceNow).

  • Basics of model deployment and ML lifecycle management.

  • Data engineering fundamentals in Databricks .

  • Ticket automations, SLA logic, and enterprise workflow routing.

  • Security best practices for enterprise AI systems.

Job Tags

Traineeship,

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