Lasso is on a mission to secure the use of LLMs in the real world protecting data, privacy, and businesses from AI threats. From the first line of code to protecting real-world data, every decision matters. If you're ready to shape the future of AI security - we would love to hear from you!

We are seeking an exceptional Full Stack Data Scientist 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.

Responsibilities:

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
• Strong background working with Large Language Models, including hands-on experience with training, fine-tuning, and deployment
• Experience in cybersecurity or security analytics is highly preferred but not strictly required for exceptional candidates with strong AI backgrounds
• Advanced proficiency in Python programming, with extensive experience using core ML libraries including scikit-learn, PyTorch, and Transformers
• Hands-on experience with LLM frameworks and tools such as LangChain, Hugging Face, OpenAI APIs, and vector databases
• 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