Modelling Resident

Frontier Lab; United States; Remote; USD 120.000 - 210.000; Vollzeit

Zusammenfassung

Frontier Lab in the United States is seeking an ML researcher/software engineer to build adaptive algorithms that learn and react in real time to product signals. You will collaborate across software, hardware, and algorithmic domains to improve system-wide efficiency and real-world impact.

The role requires a CS degree or equivalent, strong Python experience, and familiarity with PyTorch, JAX, or TensorFlow.

Qualifikationen

• Degree or equivalent CS research/engineering experience.
• Experience with Python and DL frameworks (PyTorch, JAX, or TensorFlow).
• Project experience in model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization.
• Understanding of model optimization techniques like RLHF and fine-tuning.
• Systems thinking across the full ML stack.
• Strong communication skills for remote collaboration.

Aufgaben

• Build adaptive algorithms that continuously learn and react in real-time to product signal.
• Collaborate across software, hardware, and algorithmic domains for system-wide efficiency.
• Explore new ways of capturing feedback to improve algorithmic performance.
• Focus on real-world impact and product signal to drive value.

Kenntnisse

Python

Deep learning

RLHF

Model optimization

Real-time systems

Systems thinking

Remote collaboration

Ausbildung

Degree in Computer Science or related field

Tools

PyTorch

TensorFlow

JAX

Jobbeschreibung

Responsibilities

• Build adaptive algorithms that continuously learn and react in real-time to product signal
• Collaborate across software, hardware, and algorithmic domains for system-wide efficiency
• Explore new ways of capturing feedback to improve algorithmic performance
• Focus on real-world impact and product signal to drive value

Requirements

• Degree or equivalent research/engineering experience in computer science
• Experience with Python and deep learning frameworks (PyTorch, JAX, or TensorFlow)
• Project experience in model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization
• Understanding of model optimization techniques like RLHF and fine-tuning
• Systems thinking across the full ML stack
• Strong communication skills for remote collaboration

About the Company

We are building efficient intelligence that evolves in real-time. Our vision is to create AI systems that are flexible, personalized, and accessible to everyone through continuous adaptation and efficiency.