Flow Cytometry Bioinformatics Engineer (MedDev ML)

Imubiosciences; Greater London; On-site; GBP 70,000 - 95,000; Full time

Benefits offered by this job

Bonus scheme

Pension and health insurance

Career development

Job summary

IMU Biosciences is seeking a Bioinformatics Software Engineer to drive the data engineering and annotation pipelines for an advanced clinical biomarker platform. You will implement production-grade features, manage model registries, and ensure compliance with MedDev ML standards.

You will lead automated cell-type annotation, enforce data integrity, and collaborate with ML engineers, biostatisticians, and clinicians to deliver reproducible, auditable workflows across ML partitions.

Qualifications

• Master’s or Ph.D. in Bioinformatics, Statistics, Computational Biology, Computer Science, Bioengineering, or a related quantitative field.
• 3+ years of professional experience handling flow cytometry high-throughput data in regulated, academic, or biotech settings.
• Experience with software engineering practices, code reviews, and data integrity in regulated environments.

Responsibilities

• Implement automated flow cytometry data engineering and annotation pipelines; produce reproducible features and QC reports.
• Manage model registry lifecycle: versioning, freezing, and licensing of models per regulatory standards.
• Enforce data leakage controls, maintain traceability, and review code for modularity and regulatory compliance.

Skills

Python

Machine learning

Biostatistics

Collaboration

Education

Master's or PhD in Bioinformatics or related field

Tools

Git

CI/CD

Nextflow

Docker

ML artifact tracking

Job description

IMU Biosciences is seeking a Bioinformatics Software Engineer to drive the data engineering and annotation pipelines for an advanced clinical biomarker platform. You will implement production-grade features, manage model registries, and ensure compliance with MedDev ML standards.

You will lead automated cell-type annotation, enforce data integrity, and collaborate with ML engineers, biostatisticians, and clinicians to deliver reproducible, auditable workflows across ML partitions.