Backend Engineer

Plume Design

0 - 2 years

2 - 4 Lacs

hyderabad

Posted:2 days ago| Platform:

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Skills Required

wireless networking simulation postgresql data analytics open source wifi analytics sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

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