Data / ML EngineerScalable ETL • MLOps • Deep Learning
I build production-grade data and ML systems: reliable pipelines, observable training, and warehouse-ready outputs—optimized for performance and measurable impact.
Builder mindset. Production standards.
I like ownership—reliable pipelines, observable training, and warehouse-ready outputs. Clean data contracts and measurable results.
Projects that read like case studies.
Filter by area. Expand for architecture and outcomes.
Agentic Network Security Monitor
Multi-agent threat orchestration with Isolation Forest anomaly detection + stateful memory.
Streaming Telemetry Patterns (Kafka)
Near real-time ingestion patterns with observable outputs.
Chronic Kidney Disease Prediction
ML classification with threshold tuning to reduce false positives.
Impact-first bullets.
Problem → solution → measurable outcome, with tooling signal.
Research Assistant — Organoid Image Analysis · Syracuse University
Syracuse, NY · Aug 2024 — Present
- Built end-to-end data + ML pipelines for brightfield organoid analysis (PyTorch/TensorFlow), reaching 85%+ agreement vs manual annotations.
- Containerized training/inference with Docker; orchestrated production jobs via Kubernetes; improved GPU throughput including multi-GPU workflows.
- Created reproducible Airflow workflows for scheduled ETL + retraining; exported features to BigQuery/Postgres for analytics and dashboards.
- Applied PCA + experimental design to quantify phenotypes; documented methods and enforced data integrity across iterations.
Software Engineer (Data / ML Pipelines) · Hackveda
Remote · Dec 2023 — Mar 2024
- Developed geospatial predictive pipelines with Spark/Hadoop; integrated outputs with BigQuery/Postgres for warehousing and analytics.
- Implemented ML + feature workflows in Dataiku DSS and Python, improving forecast accuracy by 22%; automated batch scoring via Airflow.
- Built streaming ingestion patterns for near real-time telemetry; surfaced KPIs in Tableau/Looker for stakeholders.
- Owned data modeling decisions (schemas, partitioning) and introduced CI practices for reliable deployments.
Software Engineer (Data Engineering) · Phemesoft (IBM Platinum Business Partner)
Remote · May 2023 — Jul 2023
- Built tracking + analytics workflows in Python/Pandas, improving order processing and delivery efficiency by 14%.
- Ran Market Basket Analysis on 50,000+ transactions; drove 20% repeat purchases and 15% loyalty improvement.
- Optimized Tableau dashboards; reduced reporting turnaround to 1 day and improved decision cycles.
- Improved data quality via schema validation + cross-team troubleshooting.
Depth over buzzwords.
Bigger type, cleaner scan, stronger grouping.
M.S. in Computer Science · Syracuse University
Graduating May 2026
- Google Professional Data Engineer (Certification).
- Hackathon 2023 — Ambiora SVKM Mukesh Patel Technology Park.
- IBM ICE DAY — Technical Poster Competition.
- Volunteer — Vineyard Church, Syracuse (Logistics & Outreach), Sep 2024 – Present.
Leadership & Community
Proof of ownership, coordination, and technical community building.
Organizing Committee — SU Agent-AI Workshop 2026 · Department of Electrical Engineering and Computer Science, Syracuse University
2026
Organized "FROM MODELS TO INTELLIGENT AI AGENTS" workshop featuring academic + industry talks on agentic systems, RL, diffusion models, and environment-driven training.
- Coordinated speaker logistics and agenda with faculty organizers.
- Supported execution of sessions and attendee experience end-to-end.
- Helped facilitate industry + research networking and knowledge-sharing.
Let’s talk.
Best way: email. I reply fast.
Email: hirenmanani25@gmail.com
LinkedIn: https://www.linkedin.com/in/hirenmanani
GitHub: https://github.com/hirenmanani