Lead AI/ML Data Scientist

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 Applied Scientist joining the AI Engineering organization, you will create ML/NLP models and Gen AI solutions that power our Data Leak Protection (DLP) and other Security products. You will provide technically guidance to ML engineers build the production systems, and help shape the long-term architecture of the AI Platform.

This is a hybrid role (3 day office) based out of our South Bay area (Palo Alto) office, and a perfect opportunity to pursue your passion on Data Science and ML engineering.

Responsibilities

• Fast-paced, hands-on execution, work with the team to set clear goals, and deliver against them

• Apply statistical and machine learning techniques to come up with creative solutions for detecting and solving problems in the enterprise security space

• Create, train and fine-tune NLP, large language and other models for use in large scale, real-time environments

• Work with the team to take model prototypes to production through the entire ML lifecycle phases: system architecture, data creation, training, inferencing and evaluation

• Help shape the architecture of the AI Models and Platform to support machine learning at scale and with optimal operational cost.

• Champion a culture of data and impact driven engineering

Requirements

• Minimum 5+ years of hands-on, technical development experience

• 5-10 years of experience mentoring and technically leading Data Science or ML Engineering teams.

• Strong expertise in Python with an 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 (preferably in security or related domain) through application of statistical and machine learning techniques.

• Proficient in training custom transformer, large language models or other deep learning models to solve complex NLP problems, and designing the ML systems to host models in production.

• BS/MS/Ph.D. in Computer Science, Applied Math a or a related technical field.

Bonus Points

• Experience working in high growth venture-backed startups

• Prior experience using AI in Security: Detection of Health, Named Entity, PII data, modeling security risk, etc.

• ML training and inferencing at scale with hands-on experience with horizontal and vertical scaling, including use of GPUs.

• Experience with prompt and context engineering for LLMs, RAG/vector databases, conversational/agentic frameworks is a plus

• Experience with ML frameworks such as Sagemaker, MLflow, Vertex AI, etc.

• Blog, teach, mentor, or help others learn outside of your day to day responsibilities

• Familiarity with AWS and managed infrastructure