Aether · 3 months ago
Machine Learning Scientist
Menlo Park, CA
Full-time
Onsite
Senior Level
$200K/yr - $270K/yrAether Biomachines is building the future of protein engineering with AI, focusing on breakthrough applications across various industries. They are seeking a Machine Learning Scientist to develop large-scale neural architectures and collaborate with biologists and chemists to drive discovery in the lab.
Artificial Intelligence (AI)Machine LearningMedical
No H1B
Responsibilities
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
Qualification
Required
PhD or equivalent experience in computer science, computational biology, physics, chemistry, or related field
Strong foundation in machine learning & deep learning, including: Transformers / PLMs (ESM, ProtBERT, MSA-transformers, etc.), 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
Preferred
Data engineering chops: Python ML stack (PyTorch, TensorFlow, JAX), cloud/HPC workflows, ML Ops tools (W&B, MLFlow)
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
Benefits
Equity
Reasonable accommodations are available upon request
Company
Aether
Aether Biomachines is an American artificial intelligence company that discovers proteins with high-impact, real-world applications.
Founded in 2017
11-50 employees
Funding
Current Stage
Early StageTotal Funding
$64.41MKey Investors
Tribe CapitalArtis Ventures
2025-12-03Series Unknown· $15M
2025-09-22Series Unknown· $0.32M
2023-08-16Series A· $49M
Leadership Team
Jay Zaveri
Co-Founder & President
Recent News
alleywatch.com
2025-12-09
Business Wire
2025-12-05
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