Research Engineer Machine Learning

You will build and optimize large-scale machine-learning systems for open-weight models. You will enhance shared training frameworks, data pipelines, and cluster tooling, or turn research ideas into scalable code within a research squad. You will build robust tools, integrate checkpoints, streamline evaluation, expose APIs, conduct distributed-training experiments, and deliver prototypes that become production components.

Responsibilities

• Build robust tools for large-scale machine-learning pipelines
• Integrate checkpoints, streamline evaluation, and expose APIs
• Conduct experiments using deep-learning techniques and distributed training
• Design, implement, and benchmark machine-learning algorithms
• Write clear and efficient Python code
• Deliver prototypes that become production-grade components

Requirements

• Master's or PhD in computer science or equivalent track record
• 4+ years working on large-scale machine-learning codebases
• PyTorch, JAX, or TensorFlow
• Distributed training
• DeepSpeed, FSDP, SLURM, or Kubernetes
• Deep learning, NLP, or LLMs
• Software testing
• Code review
• CI/CD

Benefits

• Healthcare coverage
• Parental leave
• Retirement plans
• Relocation support
• Wellness programs
• Meal allowances
• Transportation allowances