Bjak
Senior Machine Learning Engineer
Rol remoto de Senior ML Engineer con fit claro de ubicación del candidato.
Publicado22 jul 2026
Países elegibles5 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
IrlandaPoloniaPortugalEspañaSuecia
Resumen del rol
Senior Machine Learning Engineer
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
Focus
- Build core ML systems that power a proactive, long-horizon AI product.
- Own work end-to-end: data preparation, training, evaluation, inference, and iteration.
- Turn research ideas into working systems that run reliably in production.
- Debug model failures and system issues using real production signals.
- Iterate quickly: ship, measure outcomes, refine, and repeat.
- Collaborate closely with research, product, and engineering to deliver real user impact.
- Mentor and review work from other ML engineers through example and technical judgment.
- Work under real production constraints: latency, cost, reliability, and safety
Tech Stack
- Python
- PyTorch / JAX
- GPU-based training and inference systems
Ideal Experience
- You have built and shipped ML systems used by real users.
- You understand how modern ML models behave — and misbehave — in production.
- You write strong, production-quality code and think in systems, not scripts.
- You take ownership, work independently, and push work across the finish line.
- You learn fast, communicate clearly, and improve through iteration.
Outcomes
- ML models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets.
- Complex production issues are monitored, debugged, and resolved with minimal disruption.
- Training, inference, and data pipelines are robust, scalable, and maintainable over time.
- Drives measurable improvements in ML systems based on real-world signals and user feedback.
- Provides mentorship and technical guidance to peers, raising the overall ML engineering standard.
- Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals.
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