By making evidence the heart of security, we help customers stay ahead of ever-changing cyber-attacks. 

Corelight is a cybersecurity company that transforms network and cloud activity into evidence.  Evidence that elite defenders use to proactively hunt for threats, accelerate response to cyber incidents, gain complete network visibility and create powerful analytics using machine-learning and behavioral analysis tools.  Easily deployed, and available in traditional and SaaS-based formats, Corelight is the fastest-growing Network Detection and Response (NDR) platform in the industry.  And we are the only NDR platform that leverages the power of Open Source projects in addition to our own technology to deliver Intrusion Detection (IDS), Network Security Monitoring (NSM), and Smart PCAP solutions.  We sell to some of the most sensitive, mission critical large enterprises and government agencies in the world.

We are building a world class and uniquely targeted team to drive research through data science and security expertise. The ideal candidate will use their strong analytic skills and awareness of network and cloud security data to drive novel, durable, and effective threat detection.  Corelight can define the data our sensors generate, you will have the opportunity to contribute to how we extend the data itself to enable new types of analysis as
needed. You will be able to look back a year from now and say two things with pride: first, “I helped to build that.” and second, “We are generating insights that no one else in the world has achieved.”

As a Machine Learning Engineer within Corelight Labs, you will work closely with data scientists and network security experts to explore, design, build and deliver machine learning solutions for challenging network security problems. You will play a crucial role in the exploration and development of the ML capabilities powering our product offerings. 

Responsibilities

• Contribute to the full range of stages of AI/ML projects, from early explorations to productization and maintenance.
• Work closely with data scientists and network security experts to design and implement scalable ML pipelines for large datasets.
• Design and implement strategies to deploy LLMs and for fine-tuning.
• Conduct experiments, analyze results and resource consumption using various metrics and visualization techniques.
• Drive adoption of ML development best practices in code health, quality, test stability and maintainability.
• Participate in technical discussions within the Labs team and collaborate with other teams across the organization.
• Work in an Agile development team focused on exploring and delivering ML use cases.

Minimum Qualifications

• Strong appreciation for our core values: low ego results, tireless service, and applied curiosity.
• 3+ years experience developing, optimizing, troubleshooting, and maintaining large-scale machine learning systems.
• Experience in DevOps and/or MLOps: continuous integration and delivery, automation of ML workflows, and deployments to production environments.
• Understanding of data preprocessing, feature engineering and machine learning algorithms.
• Understanding of model testing and validation techniques for ensuring model quality and performance.
• Experience in Python and data science libraries (Pandas, Scikit-Learn, Keras, PyTorch, Tensorflow).
• Experience using Docker and/or Kubernetes, and containerized applications.
• Excellent communication skills to work effectively in a team.
• Degree in Computer Science or related fields, or equivalent experience.

Preferred Qualifications

• Experience adopting and using Agile development tools and methodologies, and working in a distributed team.
• Experience with local deployments and fine-tuning of LLMs
• Familiarity with the network security domain.
• Experience using feature stores and ML frameworks like Kubeflow, Cortex, Seldon, or BentoML.
• Experience in designing and implementing data pipelines using Apache Spark.
• Experience with cloud computing, especially Databricks and AWS Services (EC2, S3, Cloudwatch)
• Experience with experiment tracking and reproducibility tools.

We are proud of our culture and values - driving diversity of background and thought, low-ego results, applied curiosity and tireless service to our customers and community.  Corelight is committed to a geographically dispersed yet connected employee base with employees working from home and office locations around the world.  Fueled by an accelerating revenue stream, and investments from top-tier venture capital organizations such as Crowdstrike, Accel and Insight - we are rapidly expanding our team.  

Check us out at www.corelight.com