Neara
Overview
Full Time · Machine Learning · On-Site · USD 200000 - 275000 / year About Aether
Aether Biomachines is building the future of protein engineering with AI. Our proprietary Protein Function Model, Aetheron, unlocks entirely new classes of proteins that power breakthrough applications - from recycling plastics and breaking down “forever chemicals” to creating next-generation materials that 3D print faster and stronger than anything on the market. With real-world impact across aerospace, defense, clean energy, and beyond, Aether is where cutting-edge science meets world-changing opportunity. Mission
We’re looking for an AI/ML Research Scientist to be a foundational member of our machine learning team. You’ll apply large-scale models to protein sequence and structure data, partner closely with our biologists and chemists, and help define how cutting-edge ML drives discovery in the lab. This isn’t a siloed research role. You’ll be experimenting with transformers, CNNs, and GNNs one week, integrating AlphaFold predictions and functional assay data the next. You’ll have a straight line from models you build > data generated in our labs > products that reach the real world. While we have a list of core requirements, we’re also excited to hear from candidates who may have less professional experience but have demonstrated exceptional ability through side projects, open-source contributions, or independent research. At Aether, we hire for potential and creativity just as much as for long track records. What You’ll Do
Develop and train large-scale neural architectures (Transformers, PLMs, CNNs, GNNs) on biological sequence and structure data. Design self-supervised and multimodal representations that fuse sequence, structure, and functional assays. Source and integrate datasets from public repositories (UniProt, PDB, BRENDA, BindingDB) and proprietary high-throughput screening outputs. Build robust pipelines for data cleaning, normalization, and augmentation of noisy biological datasets. Benchmark models rigorously, reporting not just accuracy but biological interpretability and generalization. Collaborate with wet-lab teams to ensure ML insights drive experimental design and new data generation. Operate in a high-ownership, fast-iteration environment where negative results are just as valuable as breakthroughs. Core Requirements
PhD or equivalent experience in computer science, computational biology, physics, chemistry, or related field. Strong foundation in machine learning & deep learning, including: CNNs for structure/function prediction GNNs for protein structures and residue interactions Experience with distributed training, model parallelism, multi-GPU workflows Deep understanding of embeddings, self-supervised learning, and multimodal fusion Bioinformatics & computational biology literacy, including: Protein sequence/structure data (FASTA, PDB, AlphaFold outputs, MSAs) Familiarity with function datasets (binding, catalysis, mutagenesis) Awareness of sequence–structure–function relationships Understanding the limitations of crystallography vs functional assays Exceptional Candidates Will Have
Experience with protein design tools (Rosetta, RFdiffusion, ProteinMPNN). Comfort designing benchmarking experiments with statistical rigor and uncertainty quantification. Ability to translate ML outputs into hypotheses that experimental scientists can act on. Background in wet lab work or close collaboration with experimental biologists. Why Join Us?
Foundational role: Help shape the DNA of our AI/ML team. Unique data moat: Access to datasets that simply don’t exist anywhere else. Cross-disciplinary impact: Work at the interface of ML and experimental science. High ownership: Every model you build will directly shape discoveries and products. Mission with teeth: From curing disease to cleaning up the planet, your work will matter. Note
Aether Biomachines is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you’re excited about this role but don’t meet every requirement, we encourage you to apply.
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Full Time · Machine Learning · On-Site · USD 200000 - 275000 / year About Aether
Aether Biomachines is building the future of protein engineering with AI. Our proprietary Protein Function Model, Aetheron, unlocks entirely new classes of proteins that power breakthrough applications - from recycling plastics and breaking down “forever chemicals” to creating next-generation materials that 3D print faster and stronger than anything on the market. With real-world impact across aerospace, defense, clean energy, and beyond, Aether is where cutting-edge science meets world-changing opportunity. Mission
We’re looking for an AI/ML Research Scientist to be a foundational member of our machine learning team. You’ll apply large-scale models to protein sequence and structure data, partner closely with our biologists and chemists, and help define how cutting-edge ML drives discovery in the lab. This isn’t a siloed research role. You’ll be experimenting with transformers, CNNs, and GNNs one week, integrating AlphaFold predictions and functional assay data the next. You’ll have a straight line from models you build > data generated in our labs > products that reach the real world. While we have a list of core requirements, we’re also excited to hear from candidates who may have less professional experience but have demonstrated exceptional ability through side projects, open-source contributions, or independent research. At Aether, we hire for potential and creativity just as much as for long track records. What You’ll Do
Develop and train large-scale neural architectures (Transformers, PLMs, CNNs, GNNs) on biological sequence and structure data. Design self-supervised and multimodal representations that fuse sequence, structure, and functional assays. Source and integrate datasets from public repositories (UniProt, PDB, BRENDA, BindingDB) and proprietary high-throughput screening outputs. Build robust pipelines for data cleaning, normalization, and augmentation of noisy biological datasets. Benchmark models rigorously, reporting not just accuracy but biological interpretability and generalization. Collaborate with wet-lab teams to ensure ML insights drive experimental design and new data generation. Operate in a high-ownership, fast-iteration environment where negative results are just as valuable as breakthroughs. Core Requirements
PhD or equivalent experience in computer science, computational biology, physics, chemistry, or related field. Strong foundation in machine learning & deep learning, including: CNNs for structure/function prediction GNNs for protein structures and residue interactions Experience with distributed training, model parallelism, multi-GPU workflows Deep understanding of embeddings, self-supervised learning, and multimodal fusion Bioinformatics & computational biology literacy, including: Protein sequence/structure data (FASTA, PDB, AlphaFold outputs, MSAs) Familiarity with function datasets (binding, catalysis, mutagenesis) Awareness of sequence–structure–function relationships Understanding the limitations of crystallography vs functional assays Exceptional Candidates Will Have
Experience with protein design tools (Rosetta, RFdiffusion, ProteinMPNN). Comfort designing benchmarking experiments with statistical rigor and uncertainty quantification. Ability to translate ML outputs into hypotheses that experimental scientists can act on. Background in wet lab work or close collaboration with experimental biologists. Why Join Us?
Foundational role: Help shape the DNA of our AI/ML team. Unique data moat: Access to datasets that simply don’t exist anywhere else. Cross-disciplinary impact: Work at the interface of ML and experimental science. High ownership: Every model you build will directly shape discoveries and products. Mission with teeth: From curing disease to cleaning up the planet, your work will matter. Note
Aether Biomachines is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you’re excited about this role but don’t meet every requirement, we encourage you to apply.
#J-18808-Ljbffr