Founding Genomics Machine Learning Engineer

Responsibilities

• •Implement and optimize Evo2-based models for variant impact prediction (95.7% ClinVar AUROC).
• •Develop the S/P/E fusion engine combining sequence, pathway, and evidence signals.
• •Build scalable ML pipelines for features like synthetic lethality analysis and resistance prediction.
• •Collaborate on validation benchmarks for oncology use cases (e.g., BRCA1/2, multiple myeloma).
• •Optimize model inference for real-time clinical decision support.

Requirements

• ✓MS/PhD in ML, Bioinformatics, or related field with 3+ years in genomics AI.
• ✓Experience with large language models (e.g., Evo2, transformers) and genomic datasets (ClinVar, TCGA).
• ✓Proficiency in PyTorch/TensorFlow and scalable ML infrastructure (e.g., AWS SageMaker).
• ✓Strong publication record in computational biology or AI for healthcare.

Nice to Have

• +Experience with AlphaFold, ESMFold, or other structural biology models.
• +Knowledge of pathway databases (KEGG, Reactome) and evidence synthesis.
• +Experience with production ML systems serving healthcare applications.

Benefits

• ★Competitive salary and equity
• ★Health, dental, and vision insurance
• ★Flexible work arrangements
• ★Research publication support
• ★Access to advanced AI models and datasets

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