ML Researcher

Responsibilities:

• Design and implement continual learning algorithms for production systems.
• Develop sample-efficient training methods that learn from sparse interaction signals.
• Build retrieval and memory systems that adapt in real time.
• Run experiments, analyze results, and iterate quickly on research ideas.
• Optimize ML pipelines for latency and cost at scale.
• Contribute to technical direction and architecture decisions.

Requirements:

• Strong ML fundamentals: optimization, gradient methods, and neural architectures.
• 2+ years of hands-on training and deploying ML models.
• Python and PyTorch, JAX, or an equivalent framework.
• Retrieval-augmented systems or reinforcement learning.
• The ability to read a paper, implement the idea, and run a rigorous experiment.
• Publications at top ML venues: NeurIPS, ICML, ICLR, ACL, or similar.

Skills

JAX, ML, PyTorch, Python, machine learning