wagey.ggwagey.ggv1.0-0f5e85e-22-May
Browse Tech JobsCompaniesFeaturesPricingFAQs
Log InGet Started Free
Jobs/Machine Learning Engineer Role/Armis Security - Principal Machine Learning Engineer
Pro members applied to this job 36 hours before you saw itGet Pro ›
Armis Security

Armis Security - Principal Machine Learning Engineer

Remote - North America+ Equity2d ago
RemotePrincipalNAHealth InsuranceInsuranceMachine Learning EngineerPrincipalPythonPipeline ManagementAWSAzureGCPDockerKubernetes

Upload My Resume

Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT

Apply in One Click
Apply in One Click

Requirements

• 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- $250,000 • Bonus  and Pre-IPO Equity • The salary range listed does not include other forms of compensation or benefits (e.g. i.e. bonuses, commissions, stocks, health insurance benefits, etc.) offered to candidates. Visit our careers site for more information on benefits at Armis. • The choices you make in your career journey matter. You want to do interesting work in an important field while also having time to live your life, which is why we place so much value in your life-work balance. Armis sets you up for success with comprehensive health benefits, discretionary time off, paid holidays including monthly me days, and a highly inclusive and diverse workplace. Put your unique experiences and perspective to work in an environment where they will enable you to thrive, grow, and live your life with integrity.

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.

Get Started Free

No credit card. Takes 10 seconds.

Privacy·Terms··Contact·FAQ·Wagey on X