AI/ML Engineer I
About The Position
Quzara is seeking an AI/ML Engineer I to support the development, deployment, and operational support of AI-enabled applications serving federal and defense-adjacent customers. The role combines applied AI engineering with practical data science responsibilities to ensure reliable, secure, and high-performing AI systems in production environments. The engineer will collaborate with internal development teams and government customers to troubleshoot issues, resolve defects, optimize model behavior, and improve data quality across AI-driven workflows. This is a hands-on engineering role focused on implementation, support, and continuous improvement, not research or supervisory leadership. The role is full-time, Monday through Friday, 8:30 AM–5:30 PM, and requires working East Coast hours. Work is remote, with flexibility to work remotely or on-site if applicable under client return-to-office policies. Additional hours may occasionally be necessary. U.S. citizenship is required, and the candidate must be eligible for a U.S. Public Trust clearance.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- 1–3 years of professional experience in AI/ML engineering, data science, or software development.
- Strong proficiency in Python.
- Experience troubleshooting structured and unstructured data issues.
- Familiarity with data preprocessing, feature engineering, and model validation techniques.
- Hands-on experience working with OpenAI or similar LLM APIs.
- Familiarity with foundational models and smaller language models (SLMs).
- Experience with transformer-based architecture, such as Hugging Face Transformers.
- Understanding of embeddings, tokenization, fine-tuning concepts, and inference workflows.
- Experience integrating AI services into cloud environments; Azure is preferred.
- Understanding of LLMOps concepts, including model monitoring, logging, prompt iteration, and deployment workflows.
- Ability to debug model outputs and trace issues across data, prompts, and system integrations.
- Eligible for U.S. Public Trust clearance.
- U.S. citizenship is required.
- Must work East Coast hours.
Nice To Haves
- Experience implementing RAG architecture and vector-based search systems.
- Familiarity with vector databases such as FAISS, Pinecone, or Azure AI Search.
- Exposure to containerization (Docker) and CI/CD practices.
- Experience supporting AI systems in regulated or government environments.
- Understanding of model evaluation metrics and performance benchmarking.
Responsibilities
- Develop, integrate, and maintain AI/ML components within secure, production-grade applications.
- Work directly with customers and internal engineering teams to troubleshoot system behavior and resolve defects.
- Perform bug fixes, root cause analysis, and performance optimization across AI-enabled services.
- Diagnose and remediate data quality issues affecting model performance and system outputs.
- Support data preprocessing, transformation, validation, and feature engineering pipelines.
- Implement and optimize Large Language Model (LLM) integrations in secure cloud environments.
- Assist with prompt engineering, response evaluation, and model tuning.
- Support retrieval-augmented generation (RAG) pipelines and embedding workflows.
- Participate in LLMOps practices, including monitoring, logging, versioning, and performance tracking of deployed models.
- Evaluate model outputs for consistency, hallucination risk, bias, and reliability.
- Integrate AI services via REST APIs within backend systems.
- Contribute to observability, telemetry, and audit logging aligned with compliance requirements.
- Document technical implementations in accordance with secure development standards.
- Perform other duties as assigned.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
