Senior Machine Learning Engineer

Censys; United States; Remote; USD 182,000 - 228,000; Full time

Job summary

Censys is seeking a Senior Machine Learning Engineer to enhance its MLOps platform for internet security datasets. This role involves deploying machine learning models, optimizing performance, and collaborating with cross-functional teams to derive actionable insights from large-scale data. The ideal candidate will have extensive experience in machine learning, cloud platforms, and MLOps tools.

Benefits

401k match

Health insurance

Vision insurance

Dental insurance

Qualifications

• Bachelor’s degree or equivalent experience required.
• 3+ years of experience in Docker, Kubernetes, and Helm.
• Strong proficiency in Python and machine learning libraries.

Responsibilities

• Deploy and maintain containerized workloads for machine learning.
• Optimize machine learning models for latency and throughput.
• Collaborate with teams to design data pipelines for petabyte-scale data.

Skills

Python

Docker

Kubernetes

MLOps

Machine Learning

Education

Bachelor’s degree in Computer Science, Data Science, Engineering

Tools

Helm

PyTorch

Transformers

Metaflow

MLflow

Argo Workflows

Job description

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 position can beremote 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.

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 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.

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 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 + bonuseligibility 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 ourcareers 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.

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone *

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Link to LinkedIn Profile

How did you hear about us? * Select...

Do you require sponsorship to work in the US now or in the future? * Select...

How many years of experience do you have working in machine learning? *

Do you require any special accommodations during the interview process (for example disability related support)? *