SimpliSafe

Staff Machine Learning Engineer, ML Infrastructure

Boston, MA · Staff+

Sponsorship not specified$184k-$245kDetected 34 days ago

PythonRustC++Code ReviewAWSKubernetesCI/CDKafkaMachine LearningComputer VisionLLMsMLOpsIncident ResponseResearchLeadershipCommunicationCollaboration

About the role

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 built ML infrastructure before, knows where the sharp edges are, and is energized by making other teams faster and more reliable.

Drive architecture decisions for our Kubernetes-based ML platform - anchored on Ray for inference, alongside KServe, Triton, and vLLM - across real-time and batch workloads.
Lead deep technical reviews on system design, capacity planning, and reliability for the highest-stakes ML systems at SimpliSafe.
Build and operate real-time CV inference at scale
Own the design and evolution of cloud-side inference systems that process live video and events from SimpliSafe devices in real time.
Drive throughput, latency, and cost improvements (batching strategies, GPU utilization, autoscaling, multi-model serving) for production CV models.
Build the feedback loops between cloud inference, edge devices, and the data flywheel that improves model quality over time.
Partner with applied ML engineers to take new GenAI-powered product features from prototype to scaled deployment.
A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive
Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change.
Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them.

Strong production experience on AWS (EKS, S3, IAM, networking) and with Kafka, containerized deployments, CI/CD, and infrastructure-as-code.
Demonstrated experience designing and operating high-throughput, low-latency inference systems - GPU-aware scheduling, batching, autoscaling, multi-tenancy.
Strong written and verbal communication - you can make complex technical tradeoffs legible to ML scientists, product, and other infra teams.
Hands-on experience with LLM serving in production (vLLM, TGI, TensorRT-LLM, SGLang) - KV cache management, continuous batching, speculative decoding, quantization for serving.
Experience with model lifecycle tooling (MLflow, Weights & Biases, model registries, drift detection, shadow deployments).
Experience operating in environments with strong security and compliance requirements.
8+ years of software/ML engineering experience, with a clear track record of building and operating production ML systems at scale.
Solid grounding in ML fundamentals: how models are trained, evaluated, versioned, deployed, monitored, and rolled back in production.
Staff-level technical leadership: ability to drive ambiguous, cross-cutting initiatives, align senior stakeholders, and elevate the engineers around you without formal authority.
Bonus Points
Experience building real-time video or streaming ML pipelines (Kafka, Kinesis, Flink, or similar) at scale.
Background supporting CV workloads in production - model formats, GPU/accelerator tradeoffs, video codecs.

Proficiency in Python is required
experience with a systems language (Go, C++, Rust) for performance-sensitive components is a plus.
Deep expertise in cloud ML infrastructure on Kubernetes, with hands-on production experience with Ray (which powers our inference stack)
experience with KServe, Triton, vLLM, Kubeflow, Argo, or similar is a strong plus.

The target annual base pay range for this role is $183,500 to $244,600.
This target annual base pay range represents our good-faith estimate of what we expect to pay for this role.
We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually.

A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here )

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.
We regularly review our programs to ensure they remain competitive and aligned with our values.
We are committed to cultivating a diverse and inclusive workplace, and we believe our work is enriched when we incorporate a multitude of perspectives, backgrounds, and experiences.

This listing is sourced directly from SimpliSafe's careers page and normalized into a canonical job model.