Backend Engineer

Life at Plume
At Plume, we believe that technology isn't about moving faster, it's about making life's moments better. Which is why we've built the world's first, and only, open and hardware-independent service delivery platform for smart homes, small businesses, enterprises, and beyond. Our SaaS platform uses WiFi, advanced AI, and machine learning to create the future of connected spaces—and human experiences—at massive scale.

We now deliver services to over 60 million locations globally and have managed over 3 billion devices on our platform. We're expanding rapidly, pioneering a new category, and we achieved our Series F funding in just four years. Our customers include many of the world's largest Internet Service Providers (ISPs) who look to Plume to help them evolve their smart home offerings while gleaning insights from their own data.

With a bias for action and a love for being trailblazers, the team at Plume embodies a combination of relentless curiosity and imaginative innovation. We challenge ourselves to think in ways that other companies don't, work to do what should be done (rather than what can), and if we can't do it exceptionally well, we don't do it. It's how we've assembled a team of world-class builders, thinkers, and doers. And it's how we're reinventing what's possible every day.

Backend Engineer – Optimization, Data Analytics & Inference

Role Overview

We're looking for a Backend Engineer with a strong background in optimization, algorithms, and data analytics to design and implement intelligent solutions that optimize mesh Wi-Fi networks in home environments. You'll operate at the intersection of backend systems, applied optimization, large-scale data analytics, and statistical inference—developing algorithms, models, and insights that improve network performance, efficiency, and reliability for millions of connected devices.

Core Responsibilities

• Design, prototype, and productionize optimization models and algorithms to enhance mesh network topology, channel allocation, QOE improvements among others.
• Apply operations research (OR) and mathematical modeling to solve complex problems in resource allocation, scheduling, and network optimization.
• Perform large-scale data summarization, analytics, and statistical inference to extract actionable insights from telemetry and performance data.
• Translate research and mathematical formulations into robust, scalable backend services running in the cloud.
• Use simulation, and statistical analysis to validate algorithmic performance and impact.
• Collaborate with data scientists, network engineers, and platform teams to operationalize optimization and analytics models in production environments.

Technical Scope

• Integrate optimization models using Python libraries such as Gurobi within cloud-based microservices.
• Leverage data analytics tools and frameworks (e.g., SQL, Pandas, NumPy, Spark) for summarization, large-scale processing, and insight generation.
• Implement statistical inference and modeling techniques to uncover trends, correlations, and performance drivers.
• Architect and deploy scalable backend services in AWS/GCP/Azure using Kubernetes and modern DevOps practices.
• Build APIs and backend components that expose optimization, analytics, and inference results to applications and other systems.
• Ensure reliability, performance, and observability of algorithmic and analytics services through strong engineering practices.

Qualifications

• Strong programming skills in Python (Scala, Go, or Java experience a plus).
• Expertise in optimization concepts, including linear, nonlinear, and combinatorial optimization.
• Hands-on experience with optimization libraries (e.g., Pyomo, Gurobi, OR-Tools, CPLEX).
• Experience in data analytics, large-scale data summarization, and statistical inference.
• Proficiency in frameworks for distributed data processing and analysis (e.g., Spark, Dask, or Ray).
• Background in operations research, applied mathematics, or algorithms.
• Solid understanding of distributed systems, microservices, and event-driven architectures.
• Familiarity with data engineering and real-time streaming frameworks (Kafka, Pulsar, or similar).
• Proficiency in SQL and NoSQL databases (PostgreSQL, MongoDB, DynamoDB, etc.).
• Experience with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker).
• Strong mathematical foundation and analytical problem-solving skills.
• Knowledge of Wi-Fi networking fundamentals is a plus.

Nice To Have

• Experience optimizing wireless or mesh networks or other complex distributed systems.
• Background in functional programming (Scala preferred).
• Experience building APIs and backend services around optimization, analytics, or inference logic.
• Familiarity with AI-assisted developer tools (ChatGPT, Copilot, Cursor, etc.).
• Contributions to open-source optimization, analytics, or backend projects.

About Plume
As the creator of the only open, hardware-independent, cloud-controlled experience platform for ISPs and their subscribers, Plume partners with over 400 ISP customers, including some of the world's largest such as Comcast, Charter, Liberty Global, and J:COM.

Using OpenSync, the most widely supported open-source, silicon-to-cloud framework for smart spaces, Plume's software-defined network allows ISPs to decouple their service offerings from hardware and rapidly curate and deliver new services over a multi-vendor, open-platform architecture.

Plume is an equal opportunity workplace that maintains a continuing policy of nondiscrimination in all employment practices and decisions, ensuring equal employment opportunities for all qualified individuals without regard to race, color, creed, religion, sex, national origin, age, physical or mental disability, sexual orientation, gender identity, marital status, pregnancy, childbirth or related individual conditions, medical conditions (as defined by state law), military or veteran status, or any other characteristic protected by federal, state or local law.