AI/ML Engineer - DNA & RNA design

ysis of high-throughput experiments. We work in a broad range of application areas, including health, agriculture, specialty chemicals, and biosecurity.

Ginkgo recently announced a large partnership with Google Cloud to build a generative AI platform for engineering biology and for biosecurity. The Design Team is responsible for delivering best-in-class foundation and application specific models for design, analysis, and functional prediction of nucleic acid sequences, organismal phenotypes, and more.

Specific Role Description

As a Machine Learning / Artificial Intelligence (ML/AI) Engineer on Ginkgo's Design Team, you will leverage Ginkgo's wealth of proprietary sequence and experimental data to design, train, and experimentally validate novel foundation and application-specific (https://e.g. fine-tuned) AI models for application to classification and design of genes, regulatory elements, multi-gene pathways, and even genomes. In addition, you will collaborate with experts throughout the organization to identify transformational opportunities for application of AI in genetic design, as well as in analysis of phenotypic data.

We have access to nearly limitless compute capacity: CPU, GPU, or TPU. In addition, you will have access to Ginkgo's experimental platform and resulting large datasets for generating and testing hypotheses using machine learning approaches as well as informing strategic training data acquisition.

The successful candidate will bring practical experience in modern AI/ML methods, creativity in solving problems at the intersections of scientific domains, a collaborative mindset, and enthusiasm for professional growth. We are looking for someone who is equally comfortable dreaming big as rolling up their sleeves and digging through the weeds.

Responsibilities

• Foundation Model (FM) development: Conceive, develop, and validate best-in-class foundation models for DNA and/or RNA, leveraging Ginkgo's large and diverse proprietary sequencing datasets. Collaborate in cross-functional teams to design and experiment with model architectures, data models, data representations.
• Application-specific model development: Conceive, develop, and validate purpose-built models (https://e.g. fine-tuned) for a range of DNA and RNA design and prediction applications
• Influence strategic dataset acquisition: Partner with world-class experimentalists and hundreds of robots to conceive and design experiments to collect high-value training data at unprecedented scale. Influence how routine experiments are performed to maximize future learning potential.
• Influence the roadmap for AI at Ginkgo: Identify opportunities for application of AI and ML across the company, create prototypes, and contribute to overall prioritization and roadmap development for AI at Ginkgo.
• Maintain high-quality documentation of your work and discoveries, creating written reports, technical presentations for internal or external audiences, electronic lab notebooks, internal database records, code comments, and software documentation.
• Take part in something big: This is a growing team, a significant company focus, and a rapidly evolving field. You will be able to influence where things go and how they change.

Minimum Requirements

• Bachelor's degree and 4+ years, or Master's degree and 2+ years, of subsequent experience in applying AI/ML to biological applications
• Subject matter expertise in genetics, genomics, transcription, translation, or RNA biology
• Familiarity with recent literature and state of the art for large model architectures and training approaches
• Deep knowledge of AI/ML literature as applied to DNA or RNA
• Proficiency with at least one programing language (Python preferred)
• Experience with building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, or JAX

Preferred Capabilities and Experience

• PhD in artificial intelligence, computer science, synthetic biology, computational biology, genomics, bioinformatics, quantitative biology, chemical engineering, or another related field. Interdisciplinary work is strongly preferred.
• Hands-on experience (3+ years) in developing deep neural networks. Deep knowledge of currently available AI model architectures and data schemes. Perspective on advantages and drawbacks of various approaches
• Broad knowledge of state-of-art machine learning approaches to biological sequence analysis
• Significant hands-on experience in using software libraries such as tensorflow, pytorch, jax, and keras for model construction
• Exposure with ML and data orchestration and workflow engines like Airflow, Kubeflow, Flyte, or Dagster.
• Expertise in best practices for software development, including version control, code reviews, unit testing, and continuous integration. Experience in ML model management, MLOps, is a plus
• Proven track record of delivering in cross-functional teams and in project management. Excellence in scientific communication
• Enthusiasm to learn new techniques. Strong curiosity of areas of biology previously unknown to you

Total compensation for this role is market driven, with a starting salary of $90K+, as well as company stock awards. Base pay is ultimately determined based on a candidate's skills, expertise, and experience. We also offer a comprehensive benefits package including medical, dental & vision coverage, health spending accounts, voluntary benefits, leave of absence policies, Employee Assistance Program, 401(k) program with employer contribution, 8 paid holidays in addition to a full-week winter shutdown and unlimited Paid Time Off policy.

To learn more about Ginkgo, visit https://www.ginkgobioworks.com/press/ or check out some curated press below:

• What is it really like to take your company public via a SPAC? One Boston biotech shares its journey (Fortune)
• Ginkgo Bioworks resizes the definition of going big in biotech, raising $https://2.5B in a record SPAC deal that weighs in with a whopping $15B-plus valuation (Endpoints News)
• Ginkgo Bioworks CEO on scaling up Covid-19 testing: 'If we try, we can win' (CNBC)
• Ginkgo raises $70 million to ramp up COVID-19 testing for employers, universities (Boston Globe)
• Ginkgo Bioworks Redirects Its Biotech Platform to Coronavirus (Wall Street Journal)
• Ginkgo Bioworks Provides Support on Process Optimization to Moderna for COVID-19 Response (PRNewswire)
• The Life Factory: Synthetic Organisms From This $https://1.4 Billion Startup Will Revolutionize Manufacturing (Forbes)
• Synthetic Bio Pioneer Ginkgo Raises $290 Million in New Funding (Bloomberg)
• Ginkgo Bioworks raises $350 million fund for biotech spinouts (Reuters)
• Can This Company Convince You to Love GMOs? (The Atlantic)

We also feel that it's important to point out the obvious here - there's a serious lack of diversity in our industry, and that needs to change. Our goal is to help drive that change. Ginkgo is deeply committed to diversity, equity, and inclusion in all of its practices, especially when it comes to growing our team. Our culture promotes inclusion and embraces how rewarding it is to work with people from all walks of life.

We're developing a powerful biological engineering platform, so we must remain mindful of the many ways our technology can - and will - impact people around the world. We care about how our platform is used, and having a diverse team to build it gives us the best chance that it's something we'll be proud of as it continues to grow. Therefore, it's critical that we incorporate the diverse voices and visions of all those who play a role in the future of biology.

It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees, employment applicants, and EOE disability/vet.

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