Job description
Who We Are
Cobalt was founded on the belief of a fundamental human aspiration: the desire to live better and safer. It all started in 2013, when our founders realized that pentesting can be better. Today our diverse, fully remote team is committed to helping organizations of all sizes with seamless, effective and collaborative Offensive Security Testing that empower organizations to OPERATE FEARLESSLY and INNOVATE SECURELY.
Our customers can start a pentest in as little as 24 hours and integrate with advanced development cycles thanks to the powerful combination of our SaaS platform coupled with an exclusive community of testers known as the Cobalt Core. Accepting just 5% of applicants, the Cobalt Core boasts over 400 closely vetted and highly skilled testers who jointly conduct thousands of tests each year and are at the forefront of identifying and helping remediate risk across a dynamically changing attack surface.
Cobalt is an Equal Opportunity Employer and we strive to build a diverse and inclusive workforce at our company. At Cobalt we aspire to engage with diverse individuals, communities, and organizations in order to continue to nurture our unique rich diverse culture. Join our team, and be your true self to do your best work.
Description
We are seeking an experienced and pragmatic Machine Learning Engineer to join our growing Cloud Operations team. This role will focus on building and maintaining the pipelines and infrastructure that make machine learning and analytics possible in a security-focused, production-grade environment.
As a core contributor, you will work closely with data scientists, data engineers, and platform engineers to deploy and monitor ML models, build reusable pipelines, manage feature stores, and ensure robust, scalable, and secure data operations for our cybersecurity platform. You’ll play a key role in operationalizing machine learning in a way that directly enhances our AI-powered pentesting and analytics capabilities.
What You’ll Do
Model Operations & Deployment
- Design, build, and maintain reliable MLOps pipelines that support versioned, testable, and reproducible model training and deployment.
- Develop CI/CD pipelines for model promotion, validation, canary testing, and rollback.
- Automate model performance monitoring, logging, and alerting to maintain model health in production.
Data Engineering for ML
- Collaborate with Data Engineering and Data Science teams to build and maintain data pipelines, feature stores, and high-quality training datasets.
- Support the creation of ML-friendly data assets that meet latency, freshness, and accuracy requirements.
- Integrate robust data validation, lineage tracking, and quality checks throughout the pipeline.
Infrastructure & Reliability
- Define and manage scalable infrastructure for model training and inference using container orchestration platforms (e.g., Kubernetes).
- Apply infrastructure-as-code (IaC) principles to build reproducible environments for experimentation and production.
- Ensure compliance with security and privacy best practices in model and data handling.
Collaboration & Experimentation
- Work side-by-side with data scientists to enable fast experimentation while maintaining production-grade standards.
- Facilitate efficient use of GPU/TPU resources, experiment tracking tools, and model registries.
- Participate in planning, postmortems, and optimization of our ML platform to improve velocity and reliability.
You Have
- 3+ years of experience in software engineering or DevOps roles, with 1+ years focused on MLOps or ML infrastructure.
- Strong background in deploying machine learning models to production, including model versioning, rollback, and performance tracking.
- Advanced proficiency in Python, including common ML libraries (e.g., scikit-learn, MLflow, PyTorch, TensorFlow).
- Strong skills in building and maintaining data pipelines using tools like Apache Airflow, dbt, or similar.
- Experience working with cloud platforms (preferably GCP) and infrastructure tools like Docker, Kubernetes, Terraform, or Pulumi.
- Solid understanding of data engineering concepts such as batch and streaming ETL, data partitioning, and schema evolution.
- Familiarity with cybersecurity, penetration testing workflows, or secure data handling practices is a plus.
- Comfort working in an agile, fast-paced, and mission-driven startup environment
Why You Should Join Us
Grow in a passionate, rapidly expanding industry operating at the forefront of the Pentesting industry
Work directly with experienced senior leaders with ongoing mentorship opportunities
Earn competitive compensation and an attractive equity plan
Save for the future with a 401(k) program (US)
Benefit from medical, dental, vision and life insurance (US)
Leverage stipends for:
- Wellness
- Work-from-home equipment & wifi
- Learning & development
Make the most of our flexible, generous paid time off and paid parental leave
Pay Range Disclosure
Cobalt is committed to fair and equitable compensation practices. The salary range for this role is ($130,000 - $175,000) per year + equity + benefits. A candidate’s salary is determined by various factors including, but not limited to, relevant work experience, skills, and certifications. The salary range may differ in other states and may be impacted by proximity to major metropolitan cities.
Cobalt (the “Company”) is an equal opportunity employer, and we want the best available persons for every job. The Company makes employment decisions only based on merit. It is the Company’s policy to prohibit discrimination in any employment opportunity (including but not limited to recruitment, employment, promotion, salary increases, benefits, termination and all other terms and conditions of employment) based on race, color, sex, sexual orientation, gender, gender identity, gender expression, genetic information, pregnancy, religious creed, national origin, ancestry, age, physical/mental disability, medical condition, marital/domestic partner status, military and veteran status, height, weight or any other such characteristic protected by federal, state or local law. The Company is committed to complying with all applicable laws and providing equal employment opportunities. This commitment applies to all persons involved in the operations of the Company regardless of where the employee is located and prohibits unlawful discrimination by any employee of the Company.
Cobalt is an E-Verify employer. E-Verify is an Internet-based system operated by the Department of Homeland Security (DHS) in partnership with the Social Security Administration (SSA). It allows participating employers to electronically verify the employment eligibility of their newly hired employees in the United States.
