Mohammad Ummair

Mohammad Ummair

ML Systems & Distributed Training/Inference Infrastructure

mohdummair.iitb@gmail.com +91-8446856277 LinkedIn GitHub Google Scholar
Curriculum Vitae

Research Interests

ML Systems and Large-Scale Distributed Training/Inference Infrastructure — specifically: efficient model parallelism (intra- and inter-operator), communication optimization for cross-device tensor computation, LLM serving throughput and scheduling, and load-balancing for long-context training. Motivated by systems like Alpa, vLLM, and DistServe; seeking to build infrastructure that makes training and deploying large models faster, cheaper, and more scalable.

Education

Indian Institute of Technology (IIT), Bombay Jul 2021 – Jul 2023
Master of Technology, Computer Science & Engineering · CPI: 8.74/10
Mumbai, India
  • Thesis: Enhancing Robustness of Smart Contracts Through Declarations (Advisor: Prof. R.K. Shyamasundar)
  • Admission: GATE CS 2021 — All India Rank 95 out of 101,922 candidates (Top 0.1%)
  • Relevant Coursework: Advanced Blockchain Technology, Foundations of Machine Learning, Algorithms & Complexity, Design & Engineering of Computing Systems, Introduction to Blockchains & Cryptocurrencies
Government College of Engineering, Aurangabad Jul 2017 – Jul 2021
Bachelor of Engineering, Information Technology · CPI: 7.5/10
Aurangabad, India
  • Achievement: Winner, Smart India Hackathon 2020 (Process Modelling, GAIL India Pvt. Ltd.)

Publications

Enhancing Robustness of Smart Contracts Through Declarations
R.K. Shyamasundar, Mohammad Ummair, S. Borse
Springer, 2024
  • Declarative Security Framework: Proposed a novel Solidity language extension (Solidity+) that abstracts run-time monitoring via high-level declarations (NONRENTRANT, PARALLEL, ACCESS, INVAR), enabling automatic instrumentation of security logic at compile time without altering programmer-visible contract structure.
  • Transformation Pipeline: Designed and implemented a source-to-source preprocessor that semantics-preservingly transforms Solidity+ programs into hardened Solidity, embedding assertions as an on-chain proof skeleton — realizing a proof-carrying code paradigm for immutable blockchain contracts.
  • Vulnerability Taxonomy & Algorithmic Mitigations: Formally characterized six Solidity vulnerability classes — reentrancy, arithmetic overflow/underflow, unchecked send, tx.origin misuse, block.timestamp dependence, and concurrency races — and developed targeted transformation algorithms for each, covering critical failure modes responsible for the $60M DAO hack and $30M Parity wallet exploit.
  • Concurrency & Access-Order Specification: Introduced PARALLEL and NONRENTRANT declaration clauses to formally specify and enforce concurrency constraints at the language-semantics level, enabling coarse-grained concurrent invocation policies and non-reentrant guarantees without manual mutex instrumentation.
  • Comparative Evaluation: Empirically evaluated Solidity+ against leading static analysis tools (Mythril, Oyente, Manticore, Porosity) on real-world smart contract datasets, demonstrating that a declaration-driven run-time enforcement approach addresses vulnerability classes that purely static methods cannot soundly detect.
View Publication

Industry Research & Engineering Experience

Apple Inc. Jul 2023 – Present
Software Engineer — Systems & Infrastructure
Bangalore, India
  • Distributed Task Execution Framework: Designed and implemented a multi-node parallel execution system for a firmware validation pipeline serving 100+ engineers. Engineered task scheduling, inter-node communication, and load distribution logic, achieving a 30% reduction in end-to-end latency — directly analogous to worker-level scheduling in distributed ML training systems.
  • LLM Inference Pipeline Engineering: Designed and deployed an end-to-end LLM inference serving system on Apple Foundation models, engineering in-memory batching, query routing, and retrieval-augmented generation pipelines achieving 30% higher accuracy and 40% faster query resolution.
  • Queue-Based Scheduling & Latency Optimization: Built a message-queue-driven task dispatch system (RabbitMQ) with incremental execution logic that reduced average task wait time from 100s to 10s by eliminating redundant work — structurally similar to straggler mitigation in pipeline-parallel training.
  • MCP Server for Distributed Framework Access: Designed and built a Model Context Protocol (MCP) server exposing internal distributed execution framework APIs to LLM-based agents, enabling engineers to interact with and orchestrate distributed tasks through natural language.
  • Infrastructure Observability: Developed real-time telemetry and structured logging in Go and Python across distributed node infrastructure, sustaining 99.9% system reliability in production.
Tata Consultancy Services Feb 2021 – May 2021
Project Intern
India
  • Time Series Forecasting: Deployed hierarchical time series models to forecast client export demands, enabling proactive inventory management and improving demand accuracy for daily operations.
TechInvento May 2019 – Jun 2019
Machine Learning Intern
India
  • Computer Vision for Document Digitization: Built an automated CV pipeline to digitize handwritten documents, saving the client an estimated $1.5M/month; deployed as a Node.js web application for production monitoring.

Research Projects

High-Throughput LSM-Tree Storage Engine Code

Engineered a persistent Log-Structured Merge-tree optimized for write-heavy workloads with Bloom filter-based I/O elimination and tiered compaction — building intuition for storage-compute trade-offs central to ML checkpoint and activation management.

Single-Machine Linearizable Key-Value Store Code

Built a fault-tolerant KV store guaranteeing linearizable consistency and exactly-once semantics under failures via write-ahead logging and operation identifiers — grounding understanding of consistency models relevant to distributed parameter servers.

Distributed Ledger & Consensus Simulation

Simulated a multi-node P2P network with Proof-of-Work consensus and transaction propagation; benchmarked throughput, latency, and resilience under adversarial conditions, developing hands-on experience with distributed coordination protocols.

Multi-Threaded KV Server over gRPC (Course: CS744)

Implemented a concurrent client-server KV store with pluggable caching strategies and a load generator to study throughput/latency under increasing concurrency — mirroring performance analysis methodology used in ML systems evaluation.

Asset Performance Monitoring with ML (Smart India Hackathon 2020 — Winner)

Developed a real-time APM application integrating ML to optimize mechanical device performance for industrial use; selected as winning solution for GAIL India Pvt. Ltd.'s process modelling problem statement.

Teaching & Academic Service

Teaching Assistant — IIT Bombay, Department of Computer Science
Mumbai, India · 2021–2023
  • CS 765: Introduction to Blockchains, Cryptocurrencies & Smart Contracts (Prof. Vinay Ribeiro) — Conducted lab sessions, graded assignments and exams, and provided mentorship to graduate students on blockchain concepts and smart contract development.
  • CS 744: Design & Engineering of Computing Systems (Prof. Mythili Vutukuru) — Administered and graded lab assignments, conducted vivas (oral examinations), and mentored students on systems design principles.
  • CS 251: Software Systems (Prof. Amitabha Sanyal) — Assisted with lab sessions, grading, and student mentorship.
  • CS 254: Digital Logic Design Lab (Prof. Virendra Singh) — Supported practical lab instruction and student evaluations.
Prime Educator — GATE CS Preparation
Unacademy · May 2021–Jun 2021
  • Mentored a cohort of 20 students for GATE CS; designed customized daily practice problems and performance improvement plans for underperforming students.
Department Placement Coordinator & Web Secretary
IIT Bombay, Department of Computer Science · Jul 2022–Jul 2023
  • Managed end-to-end campus placement logistics for the Computer Science department across 100+ recruiting companies.
  • Maintained and updated official Computer Science department web presence.

Technical Skills

Languages Python, C++, Go, JavaScript/TypeScript, SQL, Java, C Frameworks FastAPI, Flask, React, Node.js, Haystack, LangChain, Hugging Face, gRPC Infrastructure AWS (EC2, S3), Docker, Kubernetes, PostgreSQL, MongoDB, RabbitMQ, CI/CD, Git Research Tools LaTeX, MATLAB, Solidity, EVM tooling