torsi0n

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

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

ML/LLM and systems engineer working in Python/PyTorch and Rust. 8+ years of professional experience with Python and machine learning; 5 years of production Rust. PhD in math, MSc financial economics, MSc neuroscience

Available for freelance work on:

- performance: profiling Python services, identifying bottlenecks and moving performance-critical code into Rust w/ PyO3

- LLM systems: agentic workflows with tools, planning and evaluation; inference serving w/ vLLM and TensorRT; edge inference

- Backend and data systems/data engineering: async Rust services, databases and high-throughput data pipelines.

- Quant and finance: backtesting engines, financial risk and fraud modeling

- Image and audio: applied ML, including generative models

Recent Rust projects:

- Leone: LLM inference engine written from scratch with my own CUDA/Metal kernels and a OpenAI-style server (https://github.com/t0rsion/leone)

- Holos: persistent homology/topological data analysis library with SOTA speed (https://github.com/t0rsion/holos)

B2B invoicing through my own company

Stack: Rust (Tokio, Axum/Actix, PyO3, Polars/Arrow), Python (PyTorch, NumPy/Pandas, Django/Flask), vLLM, TensorRT, Ray, Postgres, ClickHouse, Qdrant, Redis, Kafka, Docker, Kubernetes (k8s), gRPC, CUDA and Metal kernels.

Email: hn (the-at-symbol) vixe (dot) re

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

Working on my local LLM runtime Leone. It has a CPU path that verifies the CUDA kernels.

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

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

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

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

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

Remote: Yes (EU/US time zones).

Willing to relocate: Yes

Technologies: Rust, Python (PyTorch, NumPy/Pandas, Flask, Django), databases (Postgres, Mongo, Redis, ClickHouse), Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, audio processing, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

E-mail: hn [at-symbol] vixe [dot] re

Remote: Yes (EU/US time zones). Willing to relocate: Yes

Technologies: Rust, Python (PyTorch, NumPy/Pandas, Flask, Django), databases (Postgres, Mongo, Redis, ClickHouse), Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

E-mail: hn [at-symbol] vixe [dot] re

Remote: Yes (EU/US time zones). Willing to relocate: Yes

Technologies: Rust, Python (PyTorch, NumPy/Pandas, Flask, Django), SQL, Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

E-mail: hn [at-symbol] vixe [dot] re

Remote: Yes (EU/US time zones). Willing to relocate: Yes

Technologies: Rust, Python (PyTorch, NumPy/Pandas, Flask, Django), SQL, Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

E-mail: hn [at-symbol] vixe [dot] re

Remote: Yes (EU/US time zones). Willing to relocate: Yes

Technologies: Rust, Python, PyTorch, NumPy/Pandas, Flask, Django, SQL, Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

E-mail: hn [at-symbol] vixe [dot] re

Remote: Yes (EU/US time zones). Willing to relocate: Yes

Technologies: Rust, Python, PyTorch, NumPy/Pandas, Flask, Django, SQL, Docker; machine learning, deep learning

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)

Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines

Résumé/CV: available on request

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.

Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.

Remote: Yes, preferred. Flexible with EU and US time zones.

Willing to relocate: Yes

Technologies: machine learning, deep learning, Python, PyTorch, NumPy/Pandas, flask, Django, SQL, Docker, Rust

Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory), master's theses in finance and neuroscience, application of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction, LLMs, agentic frameworks

Résumé/CV: available on request

Expertise in data science and development of ML/DL models (AI) across domains (in banking/finance, for domain-specific image analysis and for neuroscience); 6+ years professionally working with Python and machine learning I'm actively exploring remote opportunities where I can apply my unique combination of skills coming from a math and developer background

Several years experience working with LLMs (deployment, fine-tuning), model embeddings and recently agentic frameworks

Open to freelance/contract work. I have my own company for billing. Open for US work.

E-mail: hn [at-symbol] vixe [dot] re