Machine Learning Engineer

Summary

Join Keeper Security, a rapidly growing cybersecurity company, as a Machine Learning Engineer on the AI & Threat Analytics team. This fully remote position, with hybrid options in El Dorado Hills, CA, or Chicago, IL, focuses on building next-generation autofill and classification models for our browser extension. You will design and deploy models to detect and analyze elevated access events and user behavior in real time, utilizing LLMs, transformers, and time-series models. This role involves building production-grade, privacy-preserving AI systems at scale, improving model performance and reliability, and collaborating with cross-functional teams. The ideal candidate will have extensive experience in ML engineering, particularly in cybersecurity, NLP, or sequence/temporal modeling. This position requires a strong understanding of MLOps and secure coding practices.

Requirements

• 5+ years of professional experience in ML engineering or research - focused on cybersecurity, NLP, or sequence/temporal modeling
• Strong coding skills in Python, JavaScript (React), or a similar language relevant to ML
• Hands-on experience with using and fine-tuning large language models, embeddings, or multilingual models for real-world cybersecurity tasks
• Proficiency with ML frameworks like TensorFlow, PyTorch, and Hugging Face Transformers
• Familiarity with MLOps, model deployment, and monitoring practices
• Experience with model validation and metrics (precision, recall, F1-score)
• Familiarity with cloud platforms (AWS, GCP, Azure)
• Knowledge of secure coding, encryption, zero-trust, and zero-knowledge principles
• Excellent problem-solving and communication skills
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related discipline, or equivalent experience
• Due to this role’s involvement in GovCloud, all applicants must be a “US Person”

Responsibilities

• Build, fine-tune, and deploy models using LLMs, transformers, and sequence architectures (e.g., Llama, Qwen, BERT, LSTM, TCN)
• Build classifiers for behavioral and temporal signals from user and system activity data
• Generate and augment datasets using synthetic, multilingual data and edge-case coverage
• Scale ML experimentation and deployment pipelines with MLOps best practices
• Create systems targeting cloud, on-prem, and self-hosted environments to support client-side inference
• Continuously improve model performance, latency, and reliability
• Implement secure, privacy-aware inference strategies aligned with zero-trust principles
• Collaborate with cross-functional teams to align ML efforts with product goals
• Write clean, maintainable code and provide comprehensive documentation

Benefits

• 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