Machine Learning Engineer

Role overview Advance machine learning systems for code generation and understanding. This role combines model development and experimentation with the engineering needed to evaluate models and serve them at low latency, including work related to inference and multi-agent orchestration.

Responsibilities - Develop and fine-tune models for code generation, completion, and analysis. - Run experiments to improve model quality and inference latency. - Create evaluation frameworks and benchmarks for code-related tasks. - Optimize model-serving systems for low-latency inference at scale. - Research and prototype approaches to coordinating multiple agents.

Requirements - Master’s or PhD in computer science, machine learning, or a related field. - At least three years of experience with large language models and transformer architectures. - Proficiency in Python, PyTorch, and machine learning experiment tooling. - Experience with model serving, optimization, and inference at scale. - Strong understanding of natural language processing and code representation learning.

Nice to have - Familiarity with CUDA, ONNX, vLLM, Ray, or Weights & Biases.