Armis Security
Cybersecurity
PrincipalMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Principal Machine Learning Engineer at Armis Security. Skills: AI Pipeline Engineering, Machine Learning Engineering. Design AI pipelines. Build AI pipelines”
Industry & Context.
Troubleshoot issues; Resolve issues
What They're Looking For.
Must Have
Bachelor's or Master's degree, Equivalent professional experience, Proven experience building AI/ML pipelines, Proficiency in Python, Familiarity with cloud platforms, Familiarity with containerization technologies, Understanding of data processing concepts, Understanding of machine learning concepts
Nice to Have
Master's degree
What You'll Do.
Maintain AI pipelines
Collaborate with data scientists
Collaborate with engineers
Implement AI solutions
Optimize AI infrastructure
Troubleshoot AI pipeline issues
Resolve AI pipeline issues
Document best practices
Maintain best practices
Collaborate with engineers
How You'll Work.
Team & Collaboration
Data scientists; Engineers
Full Job Description
Armis, the cyber exposure management & security company, protects the entire attack surface and manages an organization’s cyber risk exposure in real time. In a rapidly evolving, perimeter-less world, Armis ensures that organizations continuously see, protect and manage all critical assets - from the ground to the cloud. Armis secures Fortune 100, 200 and 500 companies as well as national governments, state and local entities to help keep critical infrastructure, economies and society stay safe and secure 24/7. Armis is a privately held company headquartered in California. AI Pipeline Engineer/ Principal Machine Learning Engineer - REMOTE Strategic Initiatives Team Armis is seeking a talented and motivated AI Pipeline Engineer to join our Strategic Initiatives team. Reporting to the Sr. Director of Engineering, this role will be instrumental in developing and optimizing our AI infrastructure. Responsibilities: Design, build, and maintain robust AI pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement cutting-edge AI solutions. Optimize existing AI infrastructure for performance, scalability, and reliability. Troubleshoot and resolve issues in the AI pipeline environment. Document and maintain best practices for AI pipeline development and deployment Develop and implement Minimum Viable Product (MVP) code for AI initiatives. Collaborate with other engineers to transition MVP code to production-ready systems. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent professional experience. Proven experience in building and managing AI/ML pipelines. Proficiency in Python and other relevant programming languages. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Strong understanding of data processing and machine learning concepts. Salary range guidance for this position is: $184,000- $250,
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