Akshith Macharla

Software engineer building ML/inference systems, native performance tooling, distributed backends, data systems, and AI applications.

M.S. Computer Science, CSU Chico ยท Dec 2026

About

I build across the systems stack: production backend services, distributed job processing, LLM inference and GPU performance experiments, data/ML pipelines, native C++ tooling, and agentic AI applications. I care most about measurable performance, correctness, and understanding how the system behaves underneath the API.

Work Experience

Feb 2026 โ€” Jun 2026
Chico, CA
Research Assistant โ€” 3D Computer Vision / Sensor Data Processing
  • Building C++/OpenCV tooling around Intel RealSense D455F RGB-D recordings for road-surface analysis and repeatable sensor-processing experiments.
  • Working with depth/color alignment, filtering, road-plane fitting, deviation maps, candidate masks, ROI measurements, overlays, and frame-level reports.
C++OpenCVIntel RealSenseLinux
Nov 2025 โ€” Feb 2026
Chico, CA
Web Developer
  • Shipped the production event website end-to-end, including landing pages, registration UX, backend integration, and deployment workflow.
  • Built the registration backend with Cloudflare Workers and D1, including schema/indexes, input validation, and idempotent email uniqueness.
TypeScriptSvelteKitTailwind CSSCloudflare WorkersD1
Dec 2021 โ€” Aug 2024
Hyderabad, India
Programmer Analyst / Associate Software Engineer
  • Built and maintained Java/Spring Boot backend services supporting 10K+ active users across policy, claims, validation, workflow, and audit-history flows.
  • Improved p95 API latency from about 250 ms to 200 ms through SQL/Hibernate and service-layer optimization; supported 99.9% availability and triaged 100+ production incidents.
JavaSpring BootPostgreSQLJUnitAWS
Edureka
Jan 2023 โ€” Jul 2023
Hyderabad, India
Data Science and Machine Learning Intern
  • Built a reproducible Pandas + SQL pipeline over 1.3M records and trained an Elastic Net logistic-regression model with temporal validation and threshold tuning for minority-class recall.
PythonPandasSQLScikit-learn

Project Areas

Hover a category to browse. On mobile, the project links stay expanded.

ML / Inference Systems
Serving, quantization, compilers, runtime behavior
Backend / Distributed
Queues, concurrency, reliability, observability
Full Stack
User-facing products, web apps, deployment
Agentic AI / RAG
Agents, grounded QA, tool calls, retrieval

Featured Projects

One representative project from each area; the category explorer above links to the broader set.

ML / Inference Systems
Distributed transformer inference experiments spanning vLLM serving, NCCL collectives, tensor-parallel communication, and PyTorch FX / torch.compile operator analysis on 2ร— A100 GPUs.
295.98 tok/s peak measured avg ยท 172.56 GB/s all-reduce ยท 252.87 GB/s broadcast
GPU / Native Performance
GPT-2-style byte-level BPE tokenizer implemented in C++ with a reusable thread pool and thread-local cache, benchmarked against tiktoken and Hugging Face Tokenizers.
2.11M tok/s at 8 threads ยท ~5ร— thread scaling ยท 91.6% of tiktoken throughput on the benchmark workload
Backend / Distributed
Flash-sale reservation backend with expiring seat holds and booking flows, using transactional PostgreSQL constraints to keep same-seat races correct under concurrent requests.
Concurrent same-seat race โ†’ exactly one hold succeeds ยท losing requests return 409 ยท Docker + CI/CD + Azure deployment
Data / ML Engineering
End-to-end batch ELT warehouse for the Olist e-commerce dataset, landing raw data in Azure Blob Storage, loading Snowflake, transforming and testing with dbt, and surfacing KPIs in Tableau.
Azure Blob โ†’ Snowflake RAW/STG/MART โ†’ dbt models + tests + docs โ†’ Tableau dashboards
Full Stack
Django/PostgreSQL marketplace for campus communities with listings, search and filters, favorites, seller messaging, meetup scheduling, reviews, moderation flows, and containerized deployment.
Agentic AI / RAG
Build-log triage agent that recognizes GCC/Clang, pytest, and TypeScript failures, extracts the first actionable error, and returns a compact fix plus rationale through the Agent Chat Protocol.
7.2K interactions ยท #2 most-used agent in the Fetch.AI track at CalHacks 12.0

Education

California State University, Chico
Dec 2026
Master of Science, Computer Science
Machine Learning ยท Computer Vision ยท Data Structures & Algorithms ยท Software Design ยท Systems coursework

Skills

Languages
C++CUDAPythonJavaTypeScriptPostgreSQL
ML Systems / Runtime
PyTorchvLLMNCCLTransformerstorch.compilePyTorch FXQuantizationNsight
Backend / Distributed
Spring BootFastAPIRabbitMQRedisPostgreSQLDockerKubernetesLinux
Data / ML Engineering
Kafka / RedpandaSparkSnowflakedbtPandasScikit-learnGrafana
AI Applications
RAGFAISSPEFT / LoRAHugging FaceMCPAgents

Open Source Contributions

Current upstream pull requests. These are intentionally separated from merged/finished project work.

Open PR
Fixes blockwise FP8 scale indexing under serial split-K so each GEMM slice uses its global K-block scales, with SM89 regression coverage across split-K 1/2/4.
Open PR
Fixes Cortex-M lowering for explicitly decomposed Transformer attention so quantized BMM, softmax, and scalar multiplication lower correctly, with Cortex-M55 FVP validation.
Open PR
Refactors Quasar low-level DEST access helpers toward the Blackhole API while preserving Quasar-specific register update behavior and adding typed destination-format handling.

Resumes

Certifications & Highlights

AWS Certified Developer โ€” Associate
Meta Backend Developer
LeetCode โ€” 1600+ contest rating
CalHacks 12.0 โ€” Chaos Reviewer reached 7.2K interactions and was the #2 most-used agent in the Fetch.AI track