Scientist I, Computation Protein Design

Alta Resource Technologies, Inc.

$140K — $175K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in Computational Biology, Bioinformatics, or Computer Science (1-3 years experience) or M.S. with 6+ years relevant industry experience
  • Hands-on experience with foundational protein models (ESM-2, AlphaFold, etc.)
  • Knowledge of protein design software (Rosetta, PyMOL, etc.)
  • Experience fine-tuning large-scale machine learning models
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX)
  • Familiarity with model evaluation methodologies
  • Solid understanding of protein structure and engineering principles

Responsibilities

  • Fine-tune and adapt foundational protein models for various engineering applications
  • Develop evaluation frameworks for assessing model performance
  • Conduct benchmarking studies for model selection in protein engineering tasks
  • Design computational experiments to validate model predictions
  • Leverage diverse data sources to enhance models and create agentic frameworks
  • Collaborate with Applied Biology team for actionable insights from models
  • Create technical documentation that outlines model assumptions and results

Benefits

  • Opportunity to lead a breakthrough program in national security and sustainability
  • Join a mission-driven, innovative team with high trust
  • Direct interaction and visibility with executive leadership
  • Comprehensive benefits package including 401(K), medical, dental, and vision plans
  • Generous paid parental and sick leave, plus flexible time off
Full Job Description
About the Role:

We are seeking a highly skilled Scientist I, Computation Protein Design to join our team and drive innovation in protein design and engineering through good data practices, robust analytical methods and machine learning. This role focuses on leveraging and optimizing foundational AI models to accelerate our protein engineering pipeline. The ideal candidate will have deep expertise in model fine-tuning, evaluation, and selection, with strong data engineering capabilities to support cutting-edge computational biology research.

Key Responsibilities:

Model Development
  • Fine-tune, adapt, and use foundational protein models (e.g., BoltzGen, ESM, OpenFold derivatives) for protein engineering applications
  • Develop and implement rigorous evaluation frameworks to assess model performance, including metrics for protein structure prediction, sequence optimization, and functional property prediction
  • Conduct comprehensive benchmarking studies to identify and recommend the most suitable foundational models for various protein engineering tasks
  • Design and execute computational experiments to validate model predictions against experimental data
  • Leverage multiple information sources (including bioinformatic, structural, simulations, and experimental performance data) to improve internal models and develop agentic frameworks

Cross-functional collaboration
  • Collaborate with the Applied Biology team to translate models into actionable insights.
  • Create technical documentation including model assumptions, equations, validation results, and recommendations.
  • Provide technical mentorship and review for junior engineers and scientists.
  • Clearly communicate technical findings, risks and recommendations to leadership and project stakeholders.

Data Management, Analysis and Integration
  • Contribute to developing data management systems that meet FAIR principles.
  • Develop analysis code to support the team in analyzing experimental data.
  • Engineer data into vectorized format for MCP integration
  • Utilize experimental data to validate and improve model development.

Required Qualifications:
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science with 1-3 years of relevant industry or post-doctoral experience, or M.S. with 6+ years of relevant industry experience
  • Hands-on experience with protein foundation models such as ESM-2, ESM-3, ProteinMPNN, RFdiffusion, AlphaFold, or similar architectures
  • Knowledge of protein design software and molecular modeling tools (Rosetta, PyMOL, Chimera)
  • Demonstrated experience fine-tuning and working with large-scale machine learning models, preferably protein or biological sequence models
  • Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX)
  • Experience with model evaluation methodologies, including cross-validation, performance metrics, and statistical analysis
  • Solid understanding of protein structure, function, and the principles of protein engineering
  • Experience with high-performance computing environments and GPU-accelerated computing
  • Strong communication skills and ability to work collaboratively in interdisciplinary teams
  • US Citizenship required.

Preferred, But Not Required:
  • Experience with workflow management tools (Nextflow, Snakemake, or similar)
  • Familiarity with cloud computing platforms (AWS, GCP, Azure) and containerization (Docker, Singularity)
  • Experience with distributed computing frameworks (Dask, Ray, Spark)
  • Track record of publications or contributions to open-source projects in computational biology or machine learning

What We Offer:
  • The opportunity to lead a breakthrough program redefining U.S. supply chain resilience in critical materials.
  • A mission-driven, high-trust team operating at the intersection of innovation, national security, and sustainability.
  • High Impact & Visibility: Direct interaction and reporting to executive leadership.
  • Competitive compensation and benefits package.
    • The starting pay range for this position is $140,000 to $175,000 commensurate with educational background and work experience.
    • Benefits including, 401(K) medical, dental, and vision plans, or equivalent, will be provided.
    • Paid parental leave, paid sick leave, flexible time off, company holidays.

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