AI Research Engineer – Applied AI

🕒 May 20

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PlexTrac

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🔒 Cybersecurity

☁️ SaaS

💰 $70M Series B on 2022-02

Cybersecurity • SaaS • AI

PlexTrac is a leading platform in the cybersecurity domain that specializes in automating pentesting reporting and vulnerability management. By aggregating data from various security tools and using AI-powered insights, PlexTrac helps organizations prioritize risks and streamline their Continuous Threat and Exposure Management (CTEM) processes. This enables security teams to identify, assess, and remediate vulnerabilities effectively, enhancing their overall security posture and operational efficiency.

📋 Description

• Build, train, and evaluate machine learning models that detect security threats and unusual system behavior • Develop and maintain production AI features: prompt orchestration, retrieval-augmented generation (RAG), model serving, and observability • Work with raw security data — logs, network traffic, event streams — to build reliable training datasets • Build and maintain automated pipelines for model performance reporting and operational workflows • Design and maintain data ingestion and transformation services used by downstream AI systems • Monitor models in production, identify performance issues, and ship fixes • Test models for accuracy, bias, and reliability before they reach production • Work closely with security analysts to understand detection requirements and translate them into model improvements • Write clean, documented code that other engineers can read and use as a basis for implementation • Contribute to engineering standards for how the team develops and deploys models • Designing distributed training environments, optimizing computational efficiency, and managing GPU clusters • Fine-tuning & Evaluation - Working with large language models (LLMs) and deep learning models using techniques like Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) • Model Safety & Alignment - Testing for vulnerabilities, mitigating biases, and ensuring models behave safely and predictably

🎯 Requirements

• 3+ years of software engineering experience with a focus on machine learning in production environments • Hands-on experience building and shipping ML models — not just training, but deploying and maintaining them • Strong Python skills and working knowledge of common ML libraries (scikit-learn, PyTorch, or TensorFlow) • Experience working with large, messy datasets — cleaning, labeling, and structuring data for model training • Familiarity with MLOps basics: versioning, monitoring, and retraining models in production • Ability to evaluate model performance clearly and explain trade-offs to non-technical teammates • Working knowledge of backend systems and API design

🏖️ Benefits

• Health insurance • Professional development opportunities