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About Nightfall:
Nightfall is the AI-native, unified data loss prevention and insider risk management platform that protects sensitive data across SaaS apps, GenAI tools, email, endpoint devices, and more. Hundreds of customers, spanning AI innovators to top 10 banks, trust Nightfall to detect and stop data exfiltration at scale. Nightfall enables organizations to innovate freely without the risks of losing intellectual property or exposing customer data. Our agentic platform helps security teams regain their time by putting data loss prevention on autopilot. With automatic remediation, security violations can be resolved automatically before they become incidents, and end-users can be automatically trained and coached in the moment to self-heal violations that they introduce.
Nightfall is backed by leading VC firms including Bain Capital Ventures (Enrique Salem - former CEO of Symantec), Venrock (early investors in Cloudflare), WestBridge Capital, Pear VC (early investors in Dropbox and Doordash), and a cadre of cybersecurity leaders including Frederic Kerrest (founder of Okta), Maynard Webb (former COO of eBay), Ryan Carlson (President of Chainguard), Kevin Mandia (founder of Mandiant), and many others.
About the role:
We are looking for an exceptional technical leader to join our growing team at Nightfall. As a senior, hands-on, ML engineer joining the AI Engineering organization, you will drive execution, provide solid technical expertise, raise the bar of the team, and contribute towards shaping the long-term architecture of the AI platform that powers our Data Leak Protection (DLP) and other Security products.
This is a hybrid role (3 day office) based out of our South Bay area (Palo Alto) office.
Responsibilities
Drive great execution, work with the team to set clear goals, and deliver against them
Data Analysis, Machine Modeling, System Architecture and Coding to launch AI systems in production
Help shape the architecture of the AI Platform to enable the use of cutting edge ML technologies while ensuring it is scalable and reliable
Implement best of practices in a fast-paced engineering environment and champion a culture of engineering excellence and productivity
Requirements
Minimum 3+ years of hands-on, technical development experience
3-10 years of experience mentoring and technically leading Data Science or ML Engineering teams.
Strong expertise in Python with additional language such as Go, C++, Java or Rust. Knowledge of data structures and algorithms is a must.
Grounded in Data Science and Machine Learning algorithms with demonstrated business impact through training custom deep learning NLP models, and LLMs.
ML training and inferencing at scale with hands-on experience with horizontal and vertical scaling, including use of GPUs.
BS/MS/Ph.D. in Computer Science, Applied Math or a related technical field.
Bonus Points
Experience working in high growth venture-backed startups
Experience with fine-tuning LLMs, prompt and context engineering, RAG/vector databases. conversational/agentic frameworks is a plus
Prior experience using AI in Security domain
Experience with ML Ops frameworks such as Sagemaker, MLflow, etc.
Blog, teach, mentor, or help others learn outside of your day to day responsibilities
Familiarity with AWS and managed infrastructure
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