Job Description

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.

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

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)

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

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

The freelance researcher will be responsible for the following tasks:

Network Measurement

Measure inter-provider bandwidth and latency Organize results into structured matrices for analysis

Pricing & Resource Data Collection

Collect GPU pricing and network egress pricing from cloud providers Document provider-specific constraints and assumptions

Analytical Modelling

Assist in modelling distributed training communication traffic Develop feasibility constraints based on bandwidth and synchronization limits Support compute and network cost modelling

Static Placement Framework Implementation

Implement a static, network-aware GPU placement optimizer Integrate feasibility constraints into the optimization logic

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

Research Documentation

Maintain clean, reproducible code and experiment documentation Assist in preparing figures, tables, and methodology descriptions for a research paper

Contact Detail :

95661 33822

Job Types: Part-time, Freelance
Contract length: 1 month

Pay: ₹15,000.00 - ₹20,000.00 per month

Benefits:

Flexible schedule Work from home
Work Location: Remote