Machine Learning Engineer, PEDM

Keeper Security, Inc.; Cameron Park (CA); Remote; USD 120,000 - 160,000; Full time

Job summary

A cutting-edge cybersecurity company is seeking a skilled Machine Learning Engineer to enhance their AI systems. In this fully remote role, you will be responsible for building models that enhance security operations. Join a passionate team committed to innovation in cybersecurity and help shape the future of access management.

Benefits

Medical, Dental & Vision benefits

Employer Paid Life Insurance

Voluntary Short/Long Term Disability Insurance

401k (Roth/Traditional)

Generous PTO plan

Above market annual bonuses

Qualifications

• 5+ years of professional experience in ML engineering or research.
• Strong coding skills in Python, JavaScript, or similar.
• Experience with large language models and cloud platforms.

Responsibilities

• Build, fine-tune, and deploy models using LLMs and transformers.
• Collaborate with cross-functional teams to align ML efforts with goals.
• Continuously improve model performance, latency, and reliability.

Skills

Machine Learning

Cybersecurity

Natural Language Processing

Model Validation

Problem-solving

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

TensorFlow

PyTorch

Hugging Face Transformers

Job description

We are seeking a highly motivated and experienced Machine Learning Engineer to join our AI & Threat Analytics team. 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 21 languages and is sold in over 120 countries. Join one of the fastest-growing cybersecurity companies and play a critical role in building Keeper's next-generation autofill and classification models in our browser extension.

About Keeper

Keeper Security is transforming cybersecurity for organizations globally with zero-trust privileged access management built with end-to-end encryption. Keeper’s cybersecurity solutions are FedRAMP and StateRAMP Authorized, SOC 2 compliant, FIPS 140-2 validated, as well as ISO 27001, 27017 and 27018 certified. Keeper deploys in minutes, not months, and seamlessly integrates with any tech stack to prevent breaches, reduce help desk costs and ensure compliance. Trusted by millions of individuals and thousands of organizations, Keeper is the leader for password, passkey and secrets management, privileged access, secure remote access and encrypted messaging. Learn how our zero-trust and zero-knowledge solutions defend against cyber threats at KeeperSecurity.com.

About the Role

We are seeking a passionate Machine Learning Engineer to help shape and lead innovation in Privilege Elevation and Delegation Management (PEDM). You’ll design and deploy models that detect, classify, and analyze elevated access events and user behaviors in real time. You will work on sequence and behavior modeling, temporal anomaly detection, and GenAI powered features that provide intelligent access decisions with minimal false positives, maximizing security, visibility, and usability.

This is your chance to build production-grade, privacy-preserving AI systems that operate at scale powering our product suite and backend intelligence engines with LLMs, transformers, and time-series models.

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

• 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”

• 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

Keeper Security, Inc. is an equal opportunity employer and participant in the U.S. Federal

E-Verify program. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Classification: Exempt