Freelancer Researcher – Networking Engineer (Systems Research)

Job Title: Freelancer Researcher – Networking Engineer (Systems Research) Engagement Type Freelance / Project-Based Remote Opportunity Job Purpose: The purpose of this role is to support the design, implementation, and evaluation of a measurement-informed, network-aware static placement framework (Static NOVA) for geo-localized multi-cloud GPU training. The researcher will assist in collecting real-world cloud network measurements, developing analytical cost and feasibility models, implementing optimization logic, and supporting simulation-based evaluation for a systems research study. Required Qualification: Master’s degree or PhD (completed or pursuing) in Computer Science Engineering, Information Technology, Networking / Distributed Systems. Strong academic or applied background in networking research Tools to be Familiar: Python (NumPy, Pandas, Matplotlib) Networking tools: iperf3, ping, traceroute Optimization tools or libraries (ILP solvers, OR-Tools, PuLP) Cloud platforms (at least one of AWS, GCP, Azure) Required Experience: Prior experience with systems research, cloud computing, or network performance evaluation Experience conducting measurement-based experiments (e.g., benchmarking, performance profiling) Familiarity with distributed systems concepts (latency, bandwidth, synchronization, throughput) Experience working on simulation or analytical modeling projects Prior publication experience (conference or journal) is a plus Required Knowledge/Skills: Strong understanding of: Network latency vs bandwidth trade-offs Cloud pricing models (compute and network egress pricing) Distributed machine learning communication patterns Ability to: Translate real-world measurements into analytical models Design cost and feasibility constraints Implement static optimization logic Strong analytical and problem-solving skills Ability to document methodology clearly for academic use Job Description: The freelance researcher will be responsible for the following tasks: 1. Network Measurement Measure inter-provider bandwidth and latency Organize results into structured matrices for analysis 2. Pricing & Resource Data Collection Collect GPU pricing and network egress pricing from cloud providers Document provider-specific constraints and assumptions 3. Analytical Modelling Assist in modelling distributed training communication traffic Develop feasibility constraints based on bandwidth and synchronization limits Support compute and network cost modelling 4. Static Placement Framework Implementation Implement a static, network-aware GPU placement optimizer Integrate feasibility constraints into the optimization logic 5. Simulation & Evaluation Run simulation scenarios across varying model sizes, GPU counts, and pricing conditions Compare Static NOVA against baseline placement strategies Generate plots and summaries of results 6.

Research Documentation Maintain clean, reproducible code and experiment documentation Assist in preparing figures, tables, and methodology descriptions for a research paper Contact Info: / +91 95661 33822