Computational Protein Designer & ML Engineer

InvestedintheMission; Bath Township (OH); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401K with company match

9/80 work schedule

Paid holiday shutdown

Job summary

AeroVironment seeks a Computational Protein Engineer to lead de novo protein design and optimization for metal separation technologies. You will work with machine learning, generative design tools, and large experimental datasets to drive protein performance improvements.

Join a collaborative team of scientists in a government-facing facility, with opportunities for project ownership and cross-disciplinary collaboration across computational and experimental teams.

Qualifications

• PhD in computational fields or related with strong protein design background.
• Experience with regression/optimization for large datasets and protein structure–function knowledge.
• Fluency in Python; C++/Rust for pipelines; HPC workflow automation.

Responsibilities

• Machine Learning for data analysis to generate sequences with improvements.
• Computational design using RFDiffusion, Rosetta, LigandMPNN to create novel binding pockets.
• High-throughput in-silico workflows to assess engineered protein scaffolds.
• Translate computational predictions into design parameters and collaborate with experimental team.

Skills

Regression & optimization

Protein language models

Transformer models

Python/C++/Rust

Education

PhD in Computational Chemistry/Biophysics/Protein Engineering

MS with 5+ years experience

Tools

RFDiffusion

Rosetta

LigandMPNN

Job description

AeroVironment seeks a Computational Protein Engineer to lead de novo protein design and optimization for metal separation technologies. You will work with machine learning, generative design tools, and large experimental datasets to drive protein performance improvements.

Join a collaborative team of scientists in a government-facing facility, with opportunities for project ownership and cross-disciplinary collaboration across computational and experimental teams.