Nightfall makes safeguarding sensitive data for every application simple and seamless. Organizations, from startups to global brands, trust Nightfall's software platform and APIs to discover, classify, and protect sensitive data.

We are looking for an experienced ML Platform Engineer to help build scalable production systems to improve the capacity and speed on how we develop and deploy our language models. The role requires close collaboration with Nightfall’s data & software engineers to bring more automation and scalability to our machine learning efforts. 

At Nightfall, we work with big volumes of data to detect sensitive information applying the latest ML/NLP methodologies from end to end. You will directly contribute to the core product by improving existing algorithms that highly scale in our production environment. You will ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence), and review and drive the long-term technical direction of Nightfall’s products.

Responsibilities:

• Develop distributed training infrastructure for faster training of models.
• Efficiently deploy our ML models into production.
• Create automation pipelines for continuous training, evaluation, and deployment of models.
• Improving tracking of models, data, and experiments.
• Create the interfaces, infrastructure, and clusters to process data efficiently.
• Advance monitoring to identify model drift and active learning opportunities.
• Establish scalable, efficient, automated processes for data analyses, model development, validation, and implementation.
• Collaborate with data scientists and software engineers to create and deploy new product features.
• Champion engineering excellence and culture, establish metrics for regular improvement.

Requirements:

• 4+ years of relevant work experience automating ML pipelines and deploying ML models in production environments.
• Experience designing and building systems in a microservices-based architecture
• Experience working with extremely large datasets, including collecting and preparing data, as well as training and inferencing models.
• Experience with deploying ML models as a web service and building scalable machine learning systems spanning multiple teams or organizations
• Strong foundations in ML/NLP methods and algorithms
• Extensive experience with ML deployment frameworks
• Familiarity with containerized applications, databases, and distributed computing

Bonus Points

• Experience working in high growth venture-backed startups
• Blog, teach, mentor, or help others learn outside of your day to day responsibilities

About Nightfall:

Nightfall is a cybersecurity startup dedicated to helping organizations secure and manage their sensitive data. As a leading enterprise technology company, our product affects the personal data that people entrust businesses to store & process with care every day. Critical data in modern organizations is often sprayed across a broad set of cloud data silos, and it’s a herculean task for security & compliance teams to monitor, manage, and protect this highly sensitive data. Via machine learning, our product makes it easy for organizations to discover, classify, and protect this sensitive data across their cloud footprint - such as their corporate SaaS, data infrastructure, and even their own apps. In doing so, we prevent data leakage, provide unprecedented data visibility & protection across the cloud, and enable compliance. We're a technology startup founded in San Francisco, well-funded by leading institutional investors like Bain and Venrock, and a cadre of security & IT leaders from Okta, Salesforce, Atlassian, Splunk, FireEye, and more. Learn more on our website www.nightfall.ai or by reaching out via email at [email protected].