Location: Oslo, Norway (CET)

Remote: Yes (EU/US time zones)

Willing to relocate: Yes.

Technologies: Rust, Python (PyTorch, NumPy/Pandas, Flask, Django), PyO3 Databases/infra: Postgres, ClickHouse, Qdrant, Redis, Kafka, Docker, Kubernetes (k8s) ML and systems: vLLM, TensorRT, Ray, edge ML inference, gRPC/Protobuf, systems profiling (perf, flamegraphs, Valgrind) Rust focus: Async services (Tokio, Axum/Actix), data/compute (Polars/Arrow), database proxies, performance-critical pipelines.

Domain expertise: - Academic: PhD in mathematics (topological data analysis, representation theory), MSc finance, MSc neuroscience. - Applied: database proxies/networking, quant dev and backtesting engines, ML/DL for banking & finance (risk/fraud), LLMs and agentic frameworks (tools, planning, eval), image processing, audio processing.

Résumé/CV: available upon request

Systems-oriented ML/LLM engineer specializing in Python/PyTorch and Rust for low-latency, high-throughput services. I have 8+ years of professional experience with Python and machine learning, and 5 years of production experience in Rust.

I thrive at the intersection of complex math and low-level systems. I've worked across multiple heavy domains, with deep experience building high-performance database proxies, modeling financial risk and architecting LLM agentic workflows, alongside applied work in audio and image processing. Actively exploring remote or relocation opportunities where I can apply my deep mathematical background and backend developer skills to hard engineering challenges.

Open to full-time roles or freelance/contract work (able to invoice B2B via my own company).

Email: hn [at-symbol] vixe.re