Flock Safety is looking to improve its ML platform to enable ML Engineers to research, develop, and deliver intelligence products more efficiently and safely. This includes enhancing the software, infrastructure, and systems that support the ML lifecycle, as well as improving the performance and scalability of ML inference services.
Requirements
- Strong experience with infrastructure-as-code and containerization technologies like Terraform, Packer, and Docker, ideally for building and managing robust R&D environments.
- Expertise in designing, implementing, and improving CI/CD pipelines, standardizing the full ML lifecycle from testing and image creation to release tagging and production deployment.
- Strategic understanding of ML repository architecture, knowing when to leverage a monorepo versus breaking out services into separate repositories to optimize the development lifecycle.
- Strong software engineer at heart, skilled in optimizing software for performance, testability, and extensibility, with a keen eye for identifying and remediating security vulnerabilities.
- Proficient in Python and C++, with familiarity in Go
- Standardize review and remediation process of high-risk security violations in key development projects.
- Enhance the continuous integration/continuous deployment (CI/CD) pipeline for a core development project.
Responsibilities
- Own and Extend MLOps systems: Take primary ownership of Flock’s custom MLOps tools and systems, leading its development, maintenance, and evolution.
- Own and Extend ML R&D Infrastructure: ML uses infrastructure like Packer, Terraform, Docker to allow ML Engineers to quickly create R&D environments for experimentation and development.
- Improve CI/CD of ML R&D and Production code bases: ML uses GitHub actions to trigger testing, image creation, release tagging, and production deployment.
- Update software to improve performance, testing, and extensibility
- Resolve vulnerabilities and other securities issues
- Help Production Inference: Partner with ML Engineers, Software, and SRE to improve throughput and scalability of our inference servers, and also to expand its use to support additional models
- Be the Platform Expert: Serve as the primary point of contact and technical leader for the ML team on all issues related to infrastructure, specialized build systems, and operational software.
Other
- Proven track record of owning, developing, maintaining, and evolving custom internal software tools and systems.
- A natural collaborator, adept at partnering with cross-functional ML, Software, and SRE teams to enhance the throughput and scalability of production inference servers
- You thrive as a technical leader and the go-to expert for ML infrastructure, specialized build systems, and operational software.
- If an offer is extended and accepted, this position requires the ability to obtain and maintain Criminal Justice Information Services (CJIS) certification as a condition of employment. Applicants must meet all FBI CJIS Security Policy requirements, including a fingerprint-based background check.
- We’re prioritizing candidates in our key hubs: Atlanta, Boston, Chicago, Denver, Los Angeles, New York City, San Francisco, and Austin. While we value the energy of our hub communities, we embrace remote work and welcome applications from exceptional talent across the United States.
