Censys’ mission is to be the one place to understand everything on the internet. Frustrated by the lack of trustworthy Internet intelligence, we set out to create the industry’s most comprehensive, accurate, and up-to-date map of the Internet. Today, Censys delivers real-time Internet intelligence and actionable threat insights to global governments, over 50% of the Fortune 500, and leading threat intelligence providers worldwide.
This position can be remote within the United States, but employees have the option to work from any of our office locations: Ann Arbor, MI; Los Altos, CA; Seattle, WA; or Tysons, VA.
Censys is looking for a Senior Machine Learning Engineer to join our team and help us derive valuable insights from internet security datasets. This role is responsible for building and maintaining a robust internal Machine Learning Operations (MLOps) platform capable of handling petabyte-scale data and delivering high-throughput, low-latency predictions. You will engineer and optimize this platform to support a diverse range of machine learning applications, including computer vision, natural language processing, and reinforcement learning, ensuring seamless deployment and scalability
We’re a highly collaborative, creative team dedicated to empowering customers with innovative solutions to improve their security posture. You’ll work closely with data scientists, engineers, and product teams to build scalable systems that enhance how customers interact with and understand our data. You will design machine learning systems that not only process and analyze data but also bring critical insights to the surface in a way that empowers decision-making.
What You’ll Do- Deploy and maintain containerized workloads to support machine learning development, deployment, and post-deployment monitoring.
- Utilize tools like Helm and Kustomize to accelerate the deployment of machine learning models and data pipelines.
- Apply various optimization techniques such as compilation, quantization-aware training (QAT), and pruning to improve the latency and throughput of models.
- Utilize open-source software like Metaflow, Prefect, Temporal, and Argo Workflows to facilitate data science development.
- Build and optimize machine learning models to analyze security data, extract actionable insights, and identify trends, anomalies, and other relevant security signals.
- Develop and maintain systems for drift detection and model monitoring to ensure continuous improvement and accuracy of insights.
- Collaborate with cross-functional teams to design data pipelines that can efficiently process petabytes of raw internet security data.
- Bachelor’s degree in Computer Science, Data Science, Engineering, or other technical discipline (or equivalent professional experience).
- 3+ years of experience in Docker, Kubernetes, and Helm.
- Strong proficiency in Python and machine learning libraries like PyTorch, Transformers, and Timm.
- Proficiency in MLOps tooling like Metaflow, MLflow, Argo Workflows, Torchrun, and Ray.
- Experience working with cloud platforms like AWS, GCP, and Azure.
- Experience working in the cybersecurity domain.
- Strong communication skills, including the ability to collaborate with both technical and non-technical stakeholders.
- Experience with DevOps tooling like Grafana and Prometheus.
- Proficiency in Golang and Protocol Buffers.
Our target salary range for this role is between $182,400 and $228,000 USD + bonus eligibility and equity.
In addition to our great compensation package, our benefits are effective on day one and include but are not limited to: 401k match, health, vision, dental, and more! Please see our careers page for more details.
Our innovation is fueled by the team’s global perspectives. We are open to remote employees for this role; however, we offer four hub locations that employees are welcome to use: Seattle, WA; Los Altos, CA; Tysons, VA; or Ann Arbor, MI.
Note to external recruiters/agencies: We are not currently engaging with third-party agencies for this role and will not accept unsolicited outreach. We kindly ask that you do not submit resumes or candidate profiles to our team.
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