Design and implement scalable data-processing and backend components for cybersecurity applications (threat detection, incident correlation, threat intelligence, asset management). Monitor and resolve production stability issues. Collaborate with ML researchers, UI/UX, and product management to align implementations with product needs; be assigned to a project area after interviews.
Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market.
Position Overview
We are looking for a highly skilled Staff Machine Learning Software Engineer with a passion for building robust and scalable systems to power Stellar Cyber’s Open XDR platform. In this role, you will be at the forefront of data-intensive cybersecurity and machine learning software architecture innovation, responsible for developing the foundational components that enable effective and efficient cybersecurity operations for our customers.
Key Responsibilities
- Design and implement scalable data processing components and supporting features for Stellar Cyber’s cybersecurity applications, including but not limited to, threat detections, incident correlation, threat intelligence, and asset management.
- Candidates who successfully pass all the interviews will be assigned to a project area in need.
- Monitor and resolve production stability issues related to the aforementioned components and features.
- Collaborate closely with machine learning / security researchers, UI / UX, and product management to ensure the design and implementation to align with evolving product needs and business goals.
Requirements
Minimum Qualifications
- Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
- 3 years of experience with software development or 2 years of experience with an advanced degree in an industry setting.
- 3 years of experience with data structures and algorithms in either an academic or industry setting.
- 2 years of experience with developing backend functionalities, distributed systems, APIs (REST / gRPC), and microservices for machine learning or other data intensive projects.
- Experience with cloud computing technologies, including containerization, orchestration, and deployment (Docker, Kubernetes, etc).
- Experience in one or more of the following programming languages: Python, Java, Go.
- Proficiency in communicating over a text-based medium (e.g., Slack) and can succinctly describe, discuss, and document technical details.
Preferred Qualifications
- PhD in Computer Science with a research focus on software systems.
- Experience with developing backend components, such as threat detection engines, in a cybersecurity product.
- Experience working on machine learning platform teams and/or building tools and frameworks for researchers.
- Experience with observability frameworks and practices in machine learning systems.
- Knowledge of machine learning and/or SecOps concepts is a plus.
Benefits
- Pre-IPO Stock Options (equity opportunity)
- Medical, Dental & Vision care
- Life Insurance
- 401(k)
- Employee Assistance Program
- Paid time off
- Referral Program
- Rewards and Recognition Program
Why join us?
- Work at the forefront of cybersecurity innovation within a dynamic, fast-growing team.
- Opportunity to significantly influence and shape the integration architecture of a next-generation SecOps platform powered by AI and automation.
- Competitive salary, comprehensive benefits, and ample career growth opportunities.
Top Skills
Python,Java,Go,Docker,Kubernetes,Rest,Grpc,Microservices,Containerization,Orchestration,Machine Learning
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