Who is Flock?

Flock Safety is the leading safety technology platform, helping communities thrive by taking a proactive approach to crime prevention and security. Our hardware and software suite connects cities, law enforcement, businesses, schools, and neighborhoods in a nationwide public-private safety network. Trusted by over 5,000 communities, 4,500 law enforcement agencies, and 1,000 businesses, Flock delivers real-time intelligence while prioritizing privacy and responsible innovation.

We’re a high-performance, low-ego team driven by urgency, collaboration, and bold thinking. Working at Flock means tackling big challenges, moving fast, and continuously improving. It’s intense but deeply rewarding for those who want to make an impact.

With nearly $700M in venture funding and a $7.5B valuation, we’re scaling intentionally and seeking top talent to help build the impossible. If you value teamwork, ownership, and solving tough problems, Flock could be the place for you.

The Opportunity

The Machine Learning team at Flock Safety leverages various software and infrastructure to support the development and deployment of models. This platform has been created from the effort and creativity of ML, Software, and Site Reliability Engineers. Given the current scale of ML, we are looking for a foundational Staff Software Engineer, ML Platform to solely focus on the ML platform. Your mission is to improve the software, infrastructure, and systems that enable ML Engineers to research, develop and deliver intelligence products, as well as working with Cloud Platform on maintaining and improving ML inference services. An ideal candidate has a good breadth of experience of software, infrastructure, and CI/CD around the ML space, who enjoys creating a space that allows R&D and Production services to run fast and safely.

How You'll Make an Impact

• 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.

• Improve design and security of ML software:

  • 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.

About You

• Proven track record of owning, developing, maintaining, and evolving custom internal software tools and systems.

• 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

• 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.

90 Days at Flock

We prescribe to a 90 day plan, believing that good days lead to good weeks, which lead to good months. This serves as a preview of the 90 day plan you will receive if you were to be hired in this role at Flock Safety.

The First 30 Days

• 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 pr