Research Engineer (LLMs and Generative Models)
Palo Alto, CA / Abu Dhabi / Paris
Engineering /
Full Time /
On-site
Headquartered in Silicon Valley, we are a newly established start-up, where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and Biological Science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine.
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. You’ll work at the intersection of biology, machine learning, and user-facing tools, building core capabilities for autonomous agents, multimodal simulation, and model finetuning.
Key Responsibility
- Build, refine, productionize, and serve generative models and workflows for biological simulation and experiment orchestration.
- Work at the intersection of science, product, and engineering to identify problems, implement solutions, and measure their impact on AIDO.
- 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.
- Work at the intersection of science, product, and engineering to prototype end-to-end research workflows and the tools to support them.
- 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.
Qualifications
- Ph.D. or equivalent practical experience in Computer Science, Engineering, or related field. Experience in life sciences or healthcare is a plus.
- 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).
- Ability to work in a fast-moving research environment, balancing rigor with rapid prototyping.
- 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.
Preferred Qualifications
- Ph.D. degree in Computer Science, Engineering, or related field. Experience in life sciences or healthcare is a plus.
- Exposure to distributed training, model distillation, and serving infrastructure.
- Experience with multimodal or multiscale modeling (text, sequence, structure, image).
- Familiarity with biological data modalities (DNA, RNA, protein, cell imaging), associated bioinformatics tools, and their unique challenges.
- Hands-on experience with agentic systems (LangChain, AutoGPT, custom planner-executor loops).
- Strong understanding of RESTful APIs, authentication, and deployment pipelines
- 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.
Join us as we embark on this journey to redefine the future of biology and medicine.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
