SimpliSafe
home security
StaffMachineLearningEngineer,MLInfrastructure
Neural analysis suggests this role is
optimal for Lead candidates.
“Staff Machine Learning Engineer, ML Infrastructure at SimpliSafe. Skills: ML infrastructure, Kubernetes, Python, LLM serving. Set technical direction for ML infrastructure. Drive architecture decisions for ML platform”
What You'll Achieve.
making other teams faster and more reliable; improvements in throughput, latency, and cost; improves model quality over time; from prototype to scaled deployment; meaningful uplift on everyone you work with; make the platform legible and durable; platform-level improvements; how fast SimpliSafe can ship intelligent features; directly impact whether someone's home is safer
Industry & Context.
identify and remove systemic bottlenecks; drive ambiguous, cross-cutting initiatives
on-call
What They're Looking For.
Must Have
8+ years of software/ML engineering experience, building and operating production ML systems at scale, cloud ML infrastructure on Kubernetes, production experience on AWS, Kafka, containerized deployments, CI/CD, infrastructure-as-code, high-throughput, low-latency inference systems, ML fundamentals, Python, written and verbal communication
Nice to Have
KServe, Triton, vLLM, Kubeflow, Argo, Go, C++, Rust, LLM serving in production, real-time video or streaming ML pipelines, CV workloads in production, model lifecycle tooling, open source contributions, security and compliance requirements
What You'll Do.
Set technical direction for ML infrastructure
Drive architecture decisions for ML platform
Lead technical reviews
Identify and remove bottlenecks
Build and operate real-time CV inference
Own design and evolution of inference systems
Stand up LLM/GenAI serving infrastructure
Shape LLM serving in production
Partner with applied ML engineers
Raise engineering bar across Cloud ML
Establish and evangelize best practices
Own reliability and operational excellence
Lead incident response and postmortems
observability standards
How You'll Work.
Team & Collaboration
partner closely with other Staff and Principal engineers; mentor across the team; align senior stakeholders; elevate the engineers around you; written and verbal communication; make complex technical tradeoffs legible to ML scientists, product, and other infra teams; highly collaborative approach
Communication Scope
written and verbal communication
Full Job Description
About SimpliSafe We’re a high-tech home security company that’s passionate about protecting the life you’ve built and our mission of keeping Every Home Secure. And we’ve created a culture here that cares just as deeply about the career you’re building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We don’t just want you to work here. We want you to grow and thrive here. We’re embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state-of-the-art office on two core days, typically Tuesday, Wednesday, or Thursday – working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done. Why are we hiring? Well, we’re growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure. About the Role We're looking for a Staff ML Engineer to join our Cloud ML team — the team that owns both the cloud-side ML infrastructure and the applied ML research that powers SimpliSafe's intelligent home security products. This is a senior individual contributor role focused on raising the bar for how we build, deploy, and operate ML systems at scale. You'll partner closely with other Staff and Principal engineers to drive architecture, mentor across the team, and set the technical direction for our ML platform. The work spans two of our most demanding workloads: real-time computer vision inference that processes video from cameras and doorbells across our customer base, and LLM/GenAI infrastructure that will power our future generation of intelligent applications. This role is for someone who has
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