Bioinformatics Engineer – Variant

• You’ll design, build, and evaluate LLM benchmarks for genomic analysis - spanning read alignment, assembly, variant calling, GWAS, causal inference, and multiomics integration.
• Your benchmarks and evaluations will set the bar for how well AI agents can serve as analysis partners for scientists working with human genetics data.
• You’ll own the full evaluation pipeline: choosing datasets, defining failure modes, writing grading scripts, and shipping evaluations that measure real capability.
• Your work directly impacts how LLMs reason through genomic problems.

• Master's or PhD in bioinformatics, genetics, biology, statistics, or related field
• 3-5 years of hands-on research experience analyzing genomics datasets (especially human data), demonstrated through publications or industry work
• Deep expertise in at least one of: population genetics, statistical genetics, clinical genomics
• Fluency with genotyping workflows: variant calling, fine-mapping, Mendelian randomization

Demonstrates expertise in designing and evaluating LLM benchmarks for genomic analysis, with a strong focus on human genetics data and proficiency in genotyping workflows. Capable of managing the full evaluation pipeline, including dataset selection and performance measurement.

• Master's Or PhD In Bioinformatics
• 3-5 Years Research Experience In Genomics
• Deep Expertise In Population Genetics
• Fluency With Genotyping Workflows
• Experience With Variant Calling

• Genomic Analysis
• Read Alignment
• Assembly
• Variant Calling
• GWAS
• Causal Inference
• Multiomics Integration
• Statistical Genetics
• Clinical Genomics

• Human Genetics Data
• Evaluation Pipeline
• Datasets
• Failure Modes
• Grading Scripts