GenBio AI is building the AI-Driven Digital Organism (AIDO) and the AIDO Virtual Lab, a platform where researchers can design, perturb, and observe biological systems entirely in silico using biological foundation models. We are looking for a Research Engineer specializing in LLMs and generative models to help us prototype, train, and productionize the AI components that power AIDO and the AIDO Virtual Lab.
Requirements
- 2+ years of experience developing, deploying, and evaluating LLMs or generative models (transformers, diffusion models, VAEs, autoregressive architectures, etc.).
- Proficiency with major deep learning frameworks such as PyTorch, HuggingFace Transformers & Accelerate, or Megatron-LM/DeepSpeed.
- Strong programming skills in Python, and modern web development frameworks, and familiarity with GPU-accelerated tools (e.g., CUDA, cuDNN, Triton).
- Familiarity with resource management and scheduling systems (e.g., SLURM, Kubernetes) and associated automation frameworks (e.g. Kubeflow, Argo Workflows, Apache Airflow, Metaflow).
- Proficiency in back-end frameworks like Django, Flask, or Node.js, and database technologies (e.g., PostgreSQL, MongoDB).
- Expertise in cloud computing (GCP, AWS).
- Familiarity with version control systems like Git and CI/CD pipelines.
Responsibilities
- Build, refine, productionize, and serve generative models and workflows for biological simulation and experiment orchestration.
- Develop APIs and pipelines for model serving, distillation, and tool integration with AIDO’s foundation models.
- Design, implement, and evaluate LLM-based agents to collaborate with users and other agents to plan virtual experiments, run studies, and synthesize knowledge.
- Support on-demand finetuning and model adaptation of foundation models with specialized datasets.
- Contribute to system robustness by improving uncertainty quantification, observability, and traceability in generative workflows.
- Maintain close attention to efficiency and scalability of models to ensure simulations are cheap, fast, and reproducible.
- Automate everything.
Other
- Ph.D. or equivalent practical experience in Computer Science, Engineering, or related field.
- Experience in life sciences or healthcare is a plus.
- Ability to work in a fast-moving research environment, balancing rigor with rapid prototyping.
- Strong communication skills, with the ability to collaborate across research, engineering, and product teams.
- Interest in building tools that democratize access to biology and empower both expert researchers and newcomers.
