Staff Software Engineer, ML Infrastructure

About the role

We're looking for a Staff Software Engineer to join our Cloud ML team. This role is for someone who has built and operated large-scale distributed services in production and is excited to bring that depth to ML infrastructure.

Qualifications

• 8+ years of software engineering experience, with a clear track record of building and operating large-scale distributed systems in production.
• Deep expertise in high-throughput, low-latency services — ad serving, recommendations, real-time APIs, online platforms, or similar — including the operational reality of running them at scale.
• Strong production experience on Kubernetes and AWS (EKS, S3, IAM, networking) and with Kafka, containerized deployments, CI/CD, and infrastructure-as-code.
• Demonstrated experience with the building blocks of high-scale systems: load balancing, autoscaling, batching, caching, multi-tenancy, queuing, and capacity planning.
• Proficiency in Python is required; experience with a systems language (Go, C++, Rust) for performance-sensitive components is a plus.
• Staff-level technical leadership: ability to drive ambiguous, cross-cutting initiatives, align senior stakeholders, and elevate the engineers around you without formal authority.
• Strong written and verbal communication — you can make complex technical tradeoffs legible to ML scientists, product, and other infra teams.
• ML exposure is preferred — having deployed or operated production ML systems, worked closely with ML teams, or built ML-adjacent infrastructure.
• Bonus Points: hands-on experience with Ray, KServe, Triton, vLLM, or other ML serving stacks; hands-on experience with LLM serving in production (vLLM, TGI, TensorRT-LLM, SGLang); experience building real-time video or streaming pipelines (Kafka, Kinesis, Flink, or similar) at scale; experience operating GPU-based inference systems — GPU-aware scheduling, multi-model serving, accelerator utilization optimization; familiarity with ML fundamentals — how models are trained, evaluated, versioned, deployed, monitored, and rolled back in production; experience with model lifecycle tooling (MLflow, Weights & Biases, model registries, drift detection, shadow deployments); open source contributions to distributed systems or ML infrastructure projects; experience operating in environments with strong security and compliance requirements.

Why This Role

The Cloud ML team owns the full surface area — infrastructure and applied research — which means your work as a Staff infra engineer directly shapes what's possible for the science. You'll have unusual leverage: the platform you build determines how fast SimpliSafe can ship intelligent features, and the features we ship directly impact whether someone's home is safer tonight than it was yesterday.

Values You'll Share

• Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them.
• Aim High - Always challenging ourselves and others to raise the bar.
• No Ego - Maintaining a "no job too small" attitude, and an open, inclusive and humble style.
• One Team - Taking a highly collaborative approach to achieving success.
• Lift As We Climb - Investing in developing others and helping others around us succeed.
• Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment.

What We Offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive.

A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families.

Free SimpliSafe system and professional monitoring for your home.

Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change.

The target annual base pay range for this role is $146,600 to $215,100. 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.

We carefully tailor individual compensation packages, including base pay, taking into consideration employees' job-related skills, experience, qualifications, work location, and other relevant business factors.

Beyond base pay, we offer a Total Rewards package that may include participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits.

We're committed to fair and equitable pay practices, as well as pay transparency. We regularly review our programs to ensure they remain competitive and aligned with our values.

We wholeheartedly embrace and actively seek applications from all individuals, no matter how they identify. 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.