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Deep Learning Protein Engineer
Posted on 5/28/2022
Everett, MA, USA
Experience Level
Desired Skills
Apache Spark
Data Analysis
  • Extensive knowledge of current neural network architectures such as transformers, convolutional neural networks, autoencoders, large language models, attention models, etc. Proficiency in supporting software libraries such as tensorflow, pytorch, keras, and scikit for model construction
  • Experience parsing large datasets and applying machine learning to develop data-driven predictive models for interpretation of biological data and industrial bioengineering
  • Enthusiasm to learn new techniques. Strong curiosity of areas of biology previously unknown to you
  • Subject matter expertise: Track, technically analyze, and summarize new developments and emerging technologies in the field of machine learning, and provide recommendations on their application to protein sciences and synthetic biology
  • Biomolecular modeling: Develop methods for applying machine learning to generate hypotheses and predictions about relationships between protein sequence, structure, dynamics, and function
  • Biological data processing: Design, build, and train deep learning models for the analysis of large datasets to critique current hypotheses, spark new ones, and provide actionable information to aid in protein design tasks
  • Model interpretation and application: Understand and predict the effects of sequence variation on protein function and biophysical parameters that are relevant for enzyme and protein engineering and improvement
  • Protein engineering: Rational design of large libraries for high-throughput experimental characterization such as activity screens, multiplexed mutagenesis assays, and display technologies
  • Technical consulting: Provide expertise on machine learning and protein engineering to support program and business development. Translate company and program goals into scientific and technical projects with clear objectives, measures of success in collaboration with other stakeholders throughout the company
  • Interdisciplinary research: Flair for collaboration between scientists, who may speak somewhat different scientific languages, but all share a common passion for synthetic biology
Desired Qualifications
  • PhD in bioengineering, computer science, biophysics, biochemistry, physics, computational biology, bioinformatics, quantitative biology, or related field. Additional experience in postgraduate research or industry research is a plus
  • Significant hands-on technical experience in applying state-of-art machine learning approaches to biological data analysis, especially within the domains of protein bioinformatics, structural biology, and biochemistry. Application of deep learning to protein engineering tasks is a plus
  • Fluency in at least one software programming language - Python strongly preferred. Familiarity of best practices for software development, including version control, code reviews, unit testing, and continuous integration. Experience in ML models management, MLOps, is a plus
  • Familiarity with at least one type of molecular modeling software such as PyMOL, Rosetta, Schrodinger, Molecular Operating Environment (MOE). Expertise in the computational modeling of biomacromolecules is a plus
Ginkgo Bioworks

501-1,000 employees

Biological engineering products developer
Company Overview
Ginkgo Bioworks’ mission is to make biology easier to engineer. The company designs custom microorganisms for customers across multiple industries.
  • Unlimited paid time off
  • Comprehensive health and parental leave benefits
  • Flexible work options
  • Commuter benefits
  • State-of-the-art labs, work spaces, and conference rooms
  • Competitive 401K contribution
Company Core Values
  • Fostering a diverse & inclusive environment
  • Promoting individual growth & career development
  • Encouraging creativity & innovation
  • Celebrating passion & drive
  • Keeping Ginkgo weird
  • Caring how our platform is used