Senior ML Researcher, Ginkgo Bioworks

• You will need to be able to handle ambiguity and uncertainty
• You will be able to influence where things go and how they change
• You will identify what needs to happen, bring it to the team’s attention, and make it happen
• You will not be expected to be an expert in All The Things
• You will be expected to have a high level of general technical competency, be a fast learner brimming with curiosity, and an expert in a few things - deep learning, in particular
• PhD in a scientific discipline including Artificial Intelligence, Computer Science and a minimum of 5 years related experience; may include post-doctoral experience; Masters and 7 years of related experience; Bachelors and 9 years of related experience; or equivalent extensive practical experience may be considered in lieu of degree
• Deep experience with Python
• Substantial knowledge of recent literature and state of the art for large model architectures and training approaches
• Experience with building and iterating on machine/deep learning models using common frameworks such as PyTorch, Tensorflow, or JAX. Demonstrated expertise in implementing and fine-tuning neural networks, including design choices such as activation functions, loss functions, and regularization techniques
• Excellent ability to explain complex technical concepts, in writing as well as verbally
• Experience with data preprocessing techniques, including feature engineering and data augmentation
• Ability to collaborate effectively with cross-functional teams, including data scientists, engineers, and domain experts
• Proficiency in using cloud computing platforms and distributed systems for training large-scale machine learning models
• Preferred Capabilities and Experience

Desirable

• As one of the first members of this new team, you will have a large role in molding our approaches to creating foundation models for biology, as well as creating fine-tuned and derived models for specific applications in bioengineering
• You will work closely with experts in DNA design and Protein Engineering to achieve this goal
• While the main focus of your work will be on building and evaluating new ML models for biology, many other types of work will come your way
• You may need to:
• Do data archaeology
• Create and debug pipelines in tools like Kubeflow or Flyte
• Quickly learn the basics of protein folding or codon optimization
• Become the company’s expert on a new tool
• Debug odd results created by a production model for a project under a time crunch
• Contribute to brainstorming
• Planning and prioritization
• Make presentations
• Give feedback on others’ proposals and code
• This is a new team, a significant company focus, and a rapidly evolving field
• Contribute to creation of new foundation models for biology
• Contribute to creating derived / fine-tuned models for specific biological applications
• Leverage Ginkgo’s extensive internally generated data, and public and in-licensed datasets of protein and DNA sequences, assay results, fermentation data time series, research archives, lab notebooks, and more
• Create processes for appropriate data featurization, model fine-tuning, benchmarks and evaluations, etc
• Work collaboratively with a team of engineers and scientists
• Create prototypes, and contribute to prioritization and roadmap development for AI at Ginkgo
• Share results and learnings through means such as whitepapers, blog posts, workshops, or presentations