Work with the CTO and a team of software development (SDE) and machine learning (ML) engineers in an agile and fast-paced environment to build ML Security Operations (MLSecOps) tools that reduce the risk inherent in Artificial Intelligence (AI) development. Architect and design scalable, robust, well-tested, and efficient solutions for ML pipelines. Work with customers and cross-functional teams to translate business requirements into technically sound solutions that serve customer use cases in the domain of ML-AI security and provenance.
Responsibilities:
1. Design, develop, and maintain software systems, applications, and services.
2. Design, build, and deploy distributed software systems in a large-scale Cloud infrastructure platform such as Amazon AWS, Google Cloud Platform, etc.
3. Develop system architectures, design data models, and implement robust communication protocols to ensure seamless collaboration among distributed components.
4. Build high-performance API services, data models, and web-application middleware with a focus on managing the overall lifecycle of the deployed application.
5. Contribute to the development of the product's user experience and feature functionality.
6. Design and deploy highly scalable Cloud deployment strategies using industry-standard infrastructure-as-code design patterns, CI/CD of software, version control, and operational scalability.
7. Design and deploy monitoring and service health/billing metrics for deployed applications.
8. Continuously improve the software development process, including testing, deployment, and monitoring.
9. Build the backend, APIs, and workflow orchestration system that power the ML security tools, as well as build and optimize Cloud-based continuous integration and continuous delivery (CI/CD) pipeline.
10. Contribute to the intellectual property of the organization and the knowledge of the greater MLSecOps community.
11. Provide technical guidance and mentoring to facilitate the professional development of junior team members.
Requirements:
Bachelor’s or equivalent degree in Computer Science, Cybersecurity, Information and Data Science or an equivalent technical field plus 5 years of progressive, post-baccalaureate experience as a software engineer, software developer, applications developer, member technical staff, programmer analyst, or equivalent; or a Master’s or equivalent degree in Computer Science, Cybersecurity, Information and Data Science or an equivalent technical field with 3 years of experience as a software engineer, software developer, applications developer, member technical staff, programmer analyst, or equivalent.
Requires 3 years of experience in a senior, principal, or lead technical role including:
1. Building and maintaining software systems;
2. Full software stack including CI/CD and DevOps practices;
3. Building distributed systems and data processing pipelines;
4. Python 3 and at least one strongly typed programming language (Go, Java, C#, and/or C++);
5. Backend systems, APIs, and state management;
6. Cloud-native technologies including containers and Kubernetes;
7. Cloud platforms (AWS, Azure, GCP and/or OCI) and Infrastructure as Code;
8. ML and MLOps, and infosec techniques.
Requires good oral and written English and interpersonal communication skills.
Must be authorized to work full-time in the U.S. without employer sponsorship.
To apply, email resume with job title in subject to Protect AI: jobs@protectai.com
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