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Applied AI/ML Engineer / Data Scientist

QUANTUM TECHNOLOGIES LLCVirginia Beach, VA🇺🇸United StatesPosted Sep 16, 2026

Quick Overview

Salary
$120.8k/yr
Seniority
Mid Senior
Work mode
Hybrid
Location
Virginia Beach, VA, United States
Posted
Yesterday
AWSMLOpsMachine LearningGenerative AILLMPython

Job Description

Job Title: Applied AI/ML Engineer / Data Scientist

Location: Virginia Beach, VA, USA

Duration: 6 Months + Extension

Bill Rate: $120,800/hour

 

Job Type: W-2 Contract

Client: To Be Discussed Later

Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Job Summary:
Key Responsibilities

  • Design, develop, evaluate, and deploy AI/ML capabilities.
  • Develop analytical models for anomaly detection, asset health, forecasting, classification, and other operational use cases.
  • Develop generative AI and agentic capabilities using enterprise-approved foundation models and AI platforms.
  • Design prompts, tools, agents, workflows, and orchestration patterns.
  • Develop Retrieval-Augmented Generation and knowledge-retrieval solutions when appropriate.
  • Create rigorous evaluation frameworks for LLM and agent behavior.
  • Establish metrics for model accuracy, relevance, reliability, hallucination, latency, and cost.
  • Develop guardrails and validation mechanisms for AI-generated responses.
  • Collaborate with Data Engineering to define training, inference, retrieval, and feature-data requirements.
  • Collaborate with the Full Stack/Cloud Engineer to deploy AI services into production.
  • Develop prototypes rapidly while designing solutions that can transition into production.
  • Monitor model and agent performance and continuously improve deployed capabilities.
  • Communicate model behavior and analytical findings to engineers, product stakeholders, and operational subject-matter experts.
  • Stay current with emerging AI, agentic AI, ML, and data-science technologies and assess their applicability.

Required Qualifications Education:A Master's degree or Bachelor's degree with equivalent experience in Computer Science, Data Science, Engineering, Statistics, Machine Learning, or a related discipline is required.
Experience:
A minimum of 4+ years of experience developing machine-learning or advanced analytics solutions is necessary. Experience taking analytical or ML solutions from experimentation into production is also required.
Technical Skills:
Strong Python skills are required, along with experience with common ML/data-science frameworks and libraries. Candidates must have a strong foundation in statistics, experimentation, model evaluation, and data analysis. Experience with cloud-based data and compute environments, APIs, software-development practices, source control, and CI/CD is also needed. A demonstrated ability to translate business or operational problems into analytical approaches is essential.

Preferred Qualifications

  • Hands-on experience developing applications using LLMs.
  • Experience with agentic frameworks, tool calling, MCP, or similar AI orchestration technologies.
  • Experience with RAG, embeddings, vector search, and knowledge-management architectures.
  • Experience implementing systematic LLM evaluation and guardrails.
  • Experience with AWS AI/ML services.
  • Experience with time-series analytics and anomaly detection.
  • Experience with industrial, energy, renewable-generation, BESS, or operational datasets.
  • Familiarity with MLOps and model-monitoring practices.

Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.

 

 

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