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Home›Jobs›Censys›Senior Machine Learning Engineer
Censys

About Censys

Empowering enterprises with attack surface visibility

🏢 Tech👥 101-200 employees📅 Founded 2017📍 Old West Side, Ann Arbor, MI💰 $103.1m⭐ 4.1
B2BEnterpriseInternet of ThingsCyber SecurityCloud Computing

Key Highlights

  • Headquartered in Ann Arbor, MI with 101-200 employees
  • Over 10% of Fortune 500 companies as clients
  • $103.1 million total funding, including $75 million in 2023
  • Triple-digit year-on-year revenue growth

Censys, headquartered in Ann Arbor, MI, is a leader in continuous attack surface management, providing enterprises with real-time visibility into global networks and devices. With over 10% of the Fortune 500 as clients, including Google, NATO, and the U.S. Department of Homeland Security, Censys has...

🎁 Benefits

Censys offers remote work opportunities, comprehensive health and wellness benefits, a 401K plan, and generous family medical leave. Employees enjoy P...

🌟 Culture

Censys fosters a culture focused on rapid innovation and engineering excellence, with a commitment to R&D and product development. The company emphasi...

🌐 Website💼 LinkedIn𝕏 TwitterAll 9 jobs →
Censys

Senior Machine Learning Engineer

Censys • Remote (US/Canada)

Posted 1 month ago🏠 RemoteSeniorMachine learning engineer
Apply Now →

Skills & Technologies

MlopsPythonComputer visionNatural language processingReinforcement learningDockerKubernetes

Job Description

Company Background

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.

Location: 

This is a remote role within the United States or Canada. 

 

Role Summary:

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 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.
  • Telepathic communication 

Qualifications:

  • 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.

Preferred Qualifications:

  • Experience working in the cyber security 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.

 

For high cost of living areas (San Francisco Bay Area, Seattle, and the New York City metro), the expected salary range for this position is $170,000 - $204,000 + bonus eligibility and equity. 

For all other locations, the expected salary range for this position is $144,000 - $174,000 + 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 roots are in Ann Arbor, Michigan and our innovation is fueled by the team’s global perspectives. For this role, we are open to remote employees across the continental US or Canada.

We value diversity and are committed to creating an inclusive environment for all employees. Censys is an equal opportunity employer.

California Privacy Rights Notice

Pursuant to the California Consumer Privacy Act (CCPA), we are providing you with notice that we collect personal information from job applicants for business purposes, including evaluating your candidacy for employment, conducting interviews, and, if applicable, completing the hiring process. The categories of information we may collect include identifiers (such as name and contact information), professional or employment-related information (such as work history, education, and references), and other information you provide in your application. We do not sell or share your personal information. For more information on how we use and protect your personal information, and your rights under the CCPA, please refer to our Privacy Policy.

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