Lasso is the AI Security Platform built for the agentic era. As organizations race to deploy AI agents and agentic applications, Lasso provides the only continuous security loop spanning discovery, AI security posture management, automated red teaming, and runtime protection. By connecting these capabilities in a single platform, Lasso gives security teams complete visibility over their AI environment, proactive risk management, next-generation adversarial testing, and real-time threat response ensuring every agent behaves within its intended scope at every stage of its lifecycle.
We are seeking an exceptional Senior Machine Learning Engineer who excels at bridging cutting-edge AI and machine learning research with practical, scalable product deployment. This role is perfect for a professional who thrives on taking full ownership of projects from conception to completion, tackling complex challenges from 0 to n at the intersection of AI and cybersecurity. The ideal candidate has a passion for not only conducting research but also transforming findings into robust, production-ready systems while driving end-to-end project delivery.
What you'll do
Research & Innovation
Research and implement state-of-the-art machine learning solutions to protect AI-powered applications, agentic workflows, and intelligent systems from sophisticated threats
Stay at the forefront of AI security research, identifying and adapting emerging ML techniques and algorithms for practical cybersecurity applications
Model Development & Deployment
Design, train, and deploy machine learning models at enterprise scale, spanning classical ML algorithms to advanced LLM pipelines
Optimize model performance across multiple dimensions including accuracy, latency, and computational cost
Apply MLOps and LLMOps best practices and methodologies to enhance security-focused AI models
Infrastructure & Engineering
Engineer robust data ingestion and inference pipelines capable of handling high-throughput production workloads
Develop and maintain scalable services using Python and FastAPI frameworks
Implement streaming data architectures and CI/CD processes that ensure models remain current and reliable in dynamic threat environments
Cross-Functional Collaboration
Partner closely with AI researchers, engineering managers, and product teams to transform innovative concepts into reliable, scalable ML systems
Collaborate with Product, Engineering, and Security teams to translate complex analytical insights into actionable, production-ready solutions
Drive rapid iteration cycles from initial prototype through full production deployment
Requirements
5+ years of combined experience in machine learning engineering and data science, with demonstrated expertise in deploying ML solutions in production environments
Advanced proficiency in Python programming, with extensive experience using core ML libraries including scikit-learn, PyTorch, and Transformers
Proficiency with data processing technologies including pandas or Polars, SQL and NoSQL databases for large-scale data handling
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies including Docker
Strong background in API development using FastAPI, microservices architecture, and building scalable backend systems
Proven ability to translate research concepts into production-grade systems with appropriate monitoring, testing, and reliability measures
Experience with MLOps practices including model versioning, experiment tracking, automated testing, and deployment pipelines
Strong analytical and problem-solving skills with attention to detail and system reliability
Track record of contributing to open source projects, publishing research, or technical writing
Nice to have
Experience in cybersecurity or security analytics
Background working with Large Language Models, including hands-on experience with training, fine-tuning, and deployment
Hands-on experience with LLM frameworks and tools such as LangChain, Hugging Face, OpenAI APIs, and vector databases