Loading...
Mid LevelFull-timePythonAWSGCPDockerMachine LearningPyTorchGitAIML
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Bioinformatics Data Engineer to join GenBio AI, a company developing multiscale foundation models to decode and simulate human biology. This role will act as the crucial bridge between raw biological data and our scalable infrastructure, ensuring data is primed for large-scale foundation model training.
Key Responsibilities
- →Source & Acquire Biological Data - Identify, evaluate, and obtain high-quality bioinformatics datasets from public and partner sources to support research and model development initiatives.
- →Deeply Understand Complex Datasets - Develop a comprehensive understanding of biological datasets, including data structures, schemas, metadata standards, entity relationships, and underlying biological context.
- →Design & Implement Data Processing Pipelines - Develop robust preprocessing scripts and scalable data transformation workflows using Python, R, and relevant tools.
- →Structure & Standardize Biological Data - Organize heterogeneous datasets into well-defined, interoperable formats aligned with internal infrastructure requirements.
- →Bioinformatics Data Analysis - Perform exploratory and statistical analysis of genomic, transcriptomic, proteomic, and other multi-omics datasets.
- →Build Data Products - Create production-ready data assets, including standardized datasets, curated releases, dashboards, analytical reports, and technical documentation.
- →Ensure Data Quality & FAIR Compliance - Curate, annotate, validate, and standardize public and partner datasets in alignment with FAIR principles.
- →Collaborate Cross-Functionally - Partner closely with research scientists and ML engineers to translate biological research needs into scalable data engineering solutions.
- →Knowledge Sharing & Documentation - Contribute domain expertise by documenting data methodologies and maintaining clear technical documentation.
Requirements
- ✓Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, Computer Science, or a related field with a heavy focus on the life sciences.
- ✓Deep, hands-on familiarity with multiple biomedical data modalities (e.g., genomics, transcriptomics, spatial omics, protein structure, biomedical imaging, clinical/phenotypic data).
- ✓Familiarity with Bioconda, Biopython, Bioconductor, samtools, bamtools, bcftools, gffutils, etc.
- ✓Strong programming skills in Python (Pandas, NumPy) and proficiency with standard bioinformatics workflow managers and tools (e.g., Ray, Kubeflow).
- ✓Experience writing clean, modular code that can be easily picked up by core data engineers for optimization in cloud environments (AWS/GCP/HF) and containerized setups (Docker).
- ✓A solid understanding of machine learning workflows and how biological data must be formatted and batched for deep learning frameworks (e.g., PyTorch).
Free to sign up. Takes 30 seconds.
