Principal Deep Learning/AI Engineer, Bioinformatics
US - California - San Diego - HQ, United States
USD 205K-307K Senior-level Full Time
Tasks
- Assess bias and edge cases across instruments and populations
- Benchmark datasets and define evaluation metrics
- Build data curation labeling and augmentation pipelines
- Design and implement AI and ML algorithms for genomics
- Develop and prototype AI models for biological data
- Ensure models are reproducible and versioned in production
- Evaluate external methods tools and collaborations
- Lead AI and bioinformatics design reviews
- Lead technical ownership of AI features in products
- Mentor scientists and engineers and provide technical guidance
- Monitor production model performance and detect regressions
- Provide technical input for regulated clinical validation
- Set coding testing and documentation standards
- Validate model performance with statistical methods
Perks/Benefits
- Dental insurance
- Family planning
- Health insurance
- Paid time off
- Retirement benefits
- Vision insurance
Skills/Tech-stack
Annotations | Anomaly Detection | Assembly | BAM | Basecalling | Bias analysis | Bioinformatics | CRAM | Case analysis | Cell analysis | Clinical validation | Data Augmentation | Data labeling | Deep learning | Edge case analysis | Error modeling | FASTQ | Genomics | Machine Learning | Metagenomics | Methylation analysis | Model Benchmarking | Model Evaluation | Monitoring | Probabilistic Modeling | Quality Control | Reference Genomes | Regression Detection | Reproducibility | Single Cell Analysis | Single-cell | Statistical validation | Traceability | VCF | Variant calling | Version control
Education
Regions
Countries
States
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