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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

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About working at 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

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 is hiring for 1 live remote role right now, listed on RemoShift and refreshed from HNWhoIsHiring. The openings span remote work, with roles open to candidates in worldwide.

Every listing on this page links to the original posting — we don't host applications, so apply directly on 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's own careers page. Roles expire when the employer removes them or age out of the index, so check back often.

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How do I apply for a remote job at 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?

Each listing on this page links to the original posting on 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's site. Click "Apply on original site" on the job card to go directly to the application — we don't host or process applications, so the employer sees your application in full.

Where are 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's remote roles open?

The live openings are open to candidates in worldwide, though specific roles may carry their own location or timezone requirements stated on the original posting.

How current is this 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 jobs list?

RemoShift refreshes HNWhoIsHiring every 30 minutes, so this list reflects what 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 is hiring for right now. Posts stay live until the employer removes them or they age out of the index.

New jobs at 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 — by email

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More roles like 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, weekly.

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