The Enigma Project at Stanford University School of Medicine aims to understand the computational principles of natural intelligence using artificial intelligence tools, and is looking for individuals to help build and fine-tune large-scale multimodal foundation models to create a foundation model of the brain.
Requirements
- 2+ years of practical experience in implementing and optimizing machine learning algorithms with distributed training using common libraries (e.g. Ray, DeepSpeed, HF Accelerate, FSDP)
- Strong programming skills in Python, with expertise in machine learning frameworks like TensorFlow or PyTorch
- Experience with orchestration platforms
- Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their machine learning services
- Familiarity with MLOps platforms (e.g. MLflow, Weights & Biases)
- Strong understanding of software engineering best practices, including version control, testing, and documentation
- Familiarity with training, fine tuning, and quantization of LLMs or multimodal models using common techniques and frameworks (LoRA, PEFT, AWQ, GPTQ, or similar)
Responsibilities
- Implement and optimize the latest machine learning algorithms/models to train multimodal foundation models on neural data
- Develop and maintain scalable, efficient, and reproducible machine-learning pipelines
- Conduct large-scale ML experiments, using the latest MLOps platforms
- Run large-scale distributed model training on high-performance computing clusters or cloud platforms
- Collaborate with machine learning researchers, data scientists, and systems engineers to ensure seamless integration of models and infrastructure
- Monitor and optimize model performance, resource utilization, and cost-effectiveness
- Stay up-to-date with the latest advancements in machine learning tools, frameworks, and methodologies
Other
- Master's degree in Computer Science or related field with 2+ years of relevant industry experience, OR Bachelor's degree with 4+ years of relevant industry experience
- Bachelor's degree and three years of relevant experience, or combination of education and relevant experience
- Thorough knowledge of the principles of engineering and related natural sciences
- Demonstrated project management experience
- Travel may be required
