AI/ML Engineer I

🕒 September 24

🇺🇸 United States – Remote

💵 $120k - $150k / year

⏰ Full Time

🟢 Junior

🤖 Machine Learning Engineer

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Quzara LLC

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2015

💼 Consulting

🏥 Healthcare

🎖️ Defense

Consulting • Healthcare • Defense

Quzara LLC is a cybersecurity firm that specializes in compliance advisory, cloud security, and managed security operations. The company's services include Federal Security & Compliance, managed detection and response, cloud security configuration audits, and vulnerability management. Quzara's mission is to provide strategic and tactical trusted advisory services to clients in both the public and private sectors, focusing on ensuring security compliance and protection against cyber threats. Notably, Quzara's Cybertorch™ service is recognized for its rigorous approach to threat monitoring and incident response, catering to standards such as FedRAMP, DoD IL-4/IL-5, and CMMC.

📋 Description

• 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 integrations in secure cloud environments • Assist with prompt engineering, response evaluation, and model tuning • Support retrieval-augmented generation 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 • Collaborate with internal development teams and government customers on reliable, secure, high-performing AI systems • Perform other duties as assigned

🎯 Requirements

• U.S. Citizenship (Required) • Bachelor's degree in Computer Science, Engineering, Data Science, or 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 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 • Experience implementing RAG architecture and vector-based search systems strongly preferred • Familiarity with vector databases, such as FAISS, Pinecone, or Azure AI Search, strongly preferred • Exposure to Docker and CI/CD practices strongly preferred • Experience supporting AI systems in regulated or government environments strongly preferred • Understanding of model evaluation metrics and performance benchmarking strongly preferred • Flexibility to work East Coast hours • Occasional additional hours may be necessary

🏖️ Benefits

• Remote work or on-site flexibility, subject to client RTO policies • Full-time salaried exempt position

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