I’m Soroosh Esmaeilian, a Machine Learning Engineer with an MSc from the University of Calgary. I build, deploy, and support production LLM applications and agent-based systems, drawing on industrial experience shipping multi-task learning anomaly detection on enterprise IoT gateways. Based in Calgary and available for relocation anywhere in Canada — also open to junior IT support and system administrator roles.
From research to production. I’ve trained models that ran on enterprise edge devices and now build software that puts language models to work.
Machine Learning Engineer with an MSc in Computer Science from the University of Calgary. As part of a three-person team, I designed and deployed an multi-task learning anomaly detection model running on IoT gateway devices for enterprise clients.
These days I build and ship production LLM and RAG systems: Claude and OpenAI APIs, LangGraph agent orchestration, pgvector embeddings, prompt engineering, and LLM evaluation, while keeping current with the fast-moving AI and software engineering stack.
Comfortable across the ML toolkit (Keras, TensorFlow) and full-stack development (Next.js, FastAPI, PostgreSQL).
I’m based in Calgary and available for relocation anywhere in Canada. Alongside ML and LLM engineering, I’m open to junior IT support and system administrator roles, backed by networking fundamentals from my MSc research in software-defined networking and by deploying and supporting my own services in production.
LLM-powered products I’ve designed, built, and shipped.
A cloud-native rebuild of Prima on Google Cloud. A seven-node LangGraph fleet, reasoning with Gemini on Vertex AI, turns plain-English questions into guarded read-only BigQuery queries over Alibaba’s 247M-sample cluster trace, routes to one of three anomaly detectors (MAD/EVT, OmniAnomaly, Chronos-Bolt), ranks the metrics behind them, and writes the briefing.
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An agentic server-health platform built on LangGraph. A fleet of Claude-driven agents writes and runs its own SQL over real server telemetry, detects anomalies, forecasts where a machine is heading, and grades its root-cause attribution against ground truth — then writes a plain-English reliability brief.
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Find organizations actually doing the R&D you care about across Canada, the US, UK, and Australia. It indexes their public research-funding history and matches it to your query, resume, or paper using hybrid vector + full-text search with an LLM reranker.
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A published Apify Actor (formerly EZrelocate) that pulls rentals from Kijiji and RentFaster in Canada, OpenRent in the UK, and Zumper in the US into one normalized, cross-source deduplicated schema. ~1.9M bundled OpenStreetMap POIs attach nearest-amenity distances to every listing, so “2-bed under $2500 within 800m of a subway” is a server-side filter. MCP-ready, so Claude can run it from a plain-English request and reason over the results.
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A Next.js app that lets anyone discover connections between notable individuals by finding instances where they appear together in a photo, either directly or through a short chain of mutual photos. Inspired by six degrees of separation.
Visit siteFrom training neural nets to wiring up agents and APIs in production.
Research and applied ML, from packet-level simulators to enterprise IoT.
Designing and shipping production AI systems end to end — PrimaV2, Granted, and a multi-country rental-data Actor on the Apify Store.
Collaboratively designed and developed EdgeInsight with a team of three, a multi-task learning anomaly detection model built in PyTorch for deployment on Litmus Edge, an IoT gateway trusted by enterprise companies.
Designed a network-wide sampling system for SDNs that adapts to dynamic flow rates. Packet-level simulations in ns-3.
Applied ML and signal processing to neuroimaging data (FNIRS, EEG) for cognitive workload and BCI classification.
Research focus: adaptive packet sampling in SDNs using ns-3 simulations.
Peer-reviewed work from my MSc research at the University of Calgary.
Open to ML engineering, LLM/RAG, and full-stack product roles, as well as junior IT support and system administrator roles. Based in Calgary, available for relocation anywhere in Canada.
I’m happy to chat about LLM architecture, RAG systems, anomaly detection, or full-stack engineering. Reach out and let’s talk.
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