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Posted Jan 27Senior Machine Learning Engineer, Cybersecurity / Threat Detection
at Keeper.app
United StatesHybrid
Responsibilities
- Design, curate, and maintain datasets for training and evaluating threat detection models
- Build custom ML models for domain-specific threat classification and risk assessment
- Engineer and optimize prompts for vision-language models to analyze session behavior
- Create evaluation frameworks and benchmarks to measure accuracy, robustness, and reliability
- Develop Python-based inference services within Dockerized environments
- Integrate AI/ML capabilities with WebSocket, WebRTC, and low-level system interfaces for real-time analysis
- Write clean, maintainable code and produce clear technical documentation
- Monitor, troubleshoot, and optimize models in production for performance, scalability, and reliability Requirements
- Manage interviews and recruitment workflow
- Lodge a complaint with your data protection authority
Requirements
- We are seeking a highly motivated and experienced Machine Learning Engineer to join our AI & Threat Analytics team.
- Join one of the fastest-growing cybersecurity companies and play a critical part in advancing Keeper’s AI-driven threat detection capabilities for our Privileged Access Management (PAM) platform. About Keeper
- Privileged accounts are prime targets for attackers, and the ML systems you build will serve as a first line of defense against anomalous and malicious behavior across SSH, RDP, VNC, and database connections.
- You will work in a Python-based environment processing real-time session data via WebSocket, WebRTC, and protocol-level interfaces.
- experience in machine learning research or development
- Strong proficiency in Python Hands-on
- experience with dataset collection, curation, and labeling for ML training •
- Experience working with vision-language models or large language models (e.g., GPT, Claude, Gemini, Qwen)
- Familiarity with prompt engineering techniques and LLM frameworks •
- Experience building and deploying ML inference systems using Docker
- Working knowledge of graph data structures and their practical applications
- Familiarity with Git-based workflows and model repositories (e.g., Hugging Face) •
- Experience using cloud platforms for ML deployment and inference (AWS, GCP, and/or Azure)
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Cybersecurity, or equivalent practical experience
- Experience with security, fraud, abuse detection, or anomaly detection systems
- Familiarity with PAM, identity, or privileged access environments
- Exposure to AWS Bedrock or similar managed AI services
- Knowledge of network protocols and low-level system interfaces Benefits
- Providing this information is optional and Keeper collects this data in order to comply with EEOC and similar requirements
Experience
- 5+ years of professional
Benefits
- This role focuses on a hybrid detection approach combining vision-language models (VLMs) and domain-adapted ML models.
- Medical, Dental & Vision (Inclusive of domestic partnerships)
- Employer Paid Life Insurance & Employee/Spouse/Child Supplemental life
- Voluntary Short/Long Term Disability Insurance
- 401k (Roth/Traditional)
- A generous PTO plan that celebrates your commitment and seniority (including paid Bereavement/Jury Duty, etc)
- Above market annual bonuses
Contact
- Learn more at KeeperSecurity.com . About the Role
Additional details
- This is a 100% remote position with an opportunity to work a hybrid schedule for candidates based in the El Dorado Hills, CA or Chicago, IL metro area!
- Keeper’s cybersecurity software is trusted by millions of people and thousands of organizations globally.
- Keeper is published in 23 languages and sold in over 150 countries.
- Keeper Security is transforming cybersecurity for people and organizations around the world.
- Keeper’s affordable and easy-to-use solutions are built on a foundation of zero-trust and zero-knowledge security to protect every user on every device.
- Our award-winning, zero-trust, privileged access management platform deploys in minutes and seamlessly integrates with any tech stack and identity application to provide visibility, security, control, reporting and compliance across an entire enterprise.
- Trusted by millions of individuals and thousands of organizations, Keeper is an innovator of best-in-class password management, secrets management, privileged access, secure remote access and encrypted messaging.
- You will tackle one of the most critical challenges in cybersecurity: detecting threats within privileged access sessions with high accuracy and low latency.
- The role is well-suited for engineers who enjoy both research-oriented work (datasets, evaluation, model training) and applied production engineering (inference systems, integration, and optimization). Responsibilities
- U.S. Person status required due to GovCloud involvement Preferred