Machine Learning Engineer (Remote)

Job summary

This role involves researching and developing next-generation AI model architectures, focusing on transitioning experimental concepts into scalable production systems. The position emphasizes collaboration with inference and systems engineers to ensure efficient deployment of new architectures.

Qualifications

• Strong foundation in machine learning and deep learning fundamentals, with practical experience in model development.
• Hands-on experience implementing neural network architectures from scratch.
• Understanding of attention mechanisms, RNNs, state-space models, and hybrid architectures.
• Knowledge of training dynamics, optimization, and architecture-level performance considerations.
• Proficiency with PyTorch or JAX for developing research-oriented ML code.
• Strong communication skills for explaining technical concepts and architectural trade-offs.

Responsibilities

• Research and develop novel neural network architectures, including alternatives to Transformers.
• Design and execute architecture-level experiments focused on scaling laws and performance trade-offs.
• Prototype models end-to-end, translating research concepts into robust implementations.
• Analyze model behavior and architectural strengths and limitations.
• Collaborate with engineering teams to ensure new architectures are scalable and deployable.
• Contribute to internal research notes, benchmarks, and open-source initiatives.

Skills

• Proficiency in machine learning frameworks (PyTorch or JAX).
• Strong analytical skills for evaluating architectural ideas through theoretical and empirical methods.
• Preferred experience with non-Transformer architectures and research-driven projects.

Education

• Relevant educational background in machine learning, computer science, or related fields is preferred.

Tools

• PyTorch, JAX, and other machine learning development tools.