Senior Machine Learning Engineer / Scientist

About Centile Bio

Centile Bioscience Inc. is a privately held company developing AI-powered quantitative neuroimaging technology to advance precision medicine in brain health. Our mission is to make objective, reproducible measurements of the brain accessible from the MRI and CT scans already acquired in routine care. Our scalable platform brings together advanced medical image processing, machine learning, population modeling, and clinical reporting.

Built to work with any scan at any age, the platform supports applications across neurological and neurodegenerative diseases, including clinical decision support, treatment monitoring, biomarker development, and patient stratification. We work with health systems, pharmaceutical and biotechnology companies, and academic research institutions bringing imaging biomarkers into research, clinical trials, and routine patient care.

We are a small, fully remote team of scientists, clinicians, engineers, commercial strategists, and operations specialists who share a commitment to rigor and reliability. As an early-stage company, every role carries real ownership. You will shape how we work, influence product direction, and see the direct impact of your contributions.

Job summary

We are seeking an experienced Senior Machine Learning Engineer to lead the technical development and production integration of complex medical imaging and machine learning workflows within our quantitative neuroimaging platform.

You will take substantial ownership of end-to-end imaging processing components, from clinical MRI input characterization and preprocessing through segmentation, quantitative feature extraction, quality control, and ML inference. You will help establish robust technical approaches for handling heterogeneous real-world imaging data and translating research algorithms into reliable, scalable software.

Working closely with our ML Scientist and ML Engineer leads, you will make technical design decisions within the imaging and ML engineering domain, optimize computational workflows, and contribute to the verification and validation of quantitative imaging methods.

This is a hands-on senior individual contributor role for an engineer who combines deep medical imaging expertise with strong software engineering practices and can independently drive complex technical initiatives. The position includes technical leadership within medical imaging and ML engineering but does not involve direct reports or formal personnel management. This role reports to the SVP of Technology.

Within the first 6 to 12 months, you will have

• Taken technical ownership of major imaging and ML processing workflows.
• Established reliable approaches for handling heterogeneous clinical MRI data.
• Improved pipeline performance, robustness, automated QC, and processing success rates.
• Led production integration or substantial optimization of one or more imaging or ML modules.
• Implemented reproducibility, provenance, and testing practices that strengthen software quality and validation readiness.
• Reduced the engineering effort required to translate research methods into production.
• Contributed technical direction that supports the scalability and maintainability of Centile's neuroimaging platform.

Job functions

Medical imaging and pipeline architecture

• Design, develop, and maintain robust end-to-end medical image processing workflows for structural brain MRI.
• Lead technical implementation of preprocessing, image registration, segmentation, quantitative feature extraction, and automated quality control.
• Design approaches for handling heterogeneous clinical MRI acquisitions, including differences in scanner vendors, sequence parameters, image quality, and anatomical coverage.
• Establish input validation, sequence identification, failure detection, and recovery strategies for imaging pipelines.
• Evaluate and integrate established neuroimaging software and emerging image processing methods.
• Optimize processing pipelines for computational performance, scalability, and reproducibility across CPU- and GPU-based environments in cloud and on-premise systems.
• Develop technical standards for imaging metadata handling, spatial consistency, processing provenance, and output validation.

Machine learning engineering and production integration

• Design and optimize ML inference pipelines and model integration workflows.
• Collaborate with ML scientists to translate experimental algorithms into maintainable, production-ready software.
• Establish approaches for model packaging, versioning, reproducibility, and deployment compatibility.
• Evaluate model robustness and performance across imaging protocols, scanners, datasets, and patient populations.
• Design and implement automated segmentation QC, outlier detection, and processing failure characterization.
• Support integration of imaging-derived measurements with normative models and downstream quantitative biomarker calculations.
• Identify technical risks associated with deploying ML models on real-world clinical data and develop mitigation strategies.

Software engineering, validation, and technical leadership

• Develop high-quality, modular, well-tested Python software and reusable imaging processing components.
• Establish automated testing strategies for imaging pipelines, including unit, integration, and regression testing.
• Design structured logging, monitoring, provenance capture, and error-handling mechanisms.
• Collaborate with platform and infrastructure engineers on scalable computational execution and deployment.
• Contribute to technical architecture discussions and make recommendations based on performance, maintainability, and reliability.
• Lead root-cause analysis and resolution of complex processing failures.
• Develop technical documentation supporting reproducibility, software verification, validation, and regulatory readiness.
• Provide technical guidance, code reviews, and mentorship to other engineers without formal personnel management responsibilities.
• Help define technical requirements and implementation strategies for new imaging biomarkers and ML processing modules.
• Maintain clear documentation of work in line with Centile Bio's Quality Management System, and complete required training on schedule.
• Handle protected health information and partner data in accordance with HIPAA, data use agreements, and Centile Bio security policies.

Qualifications

Education and experience

• Bachelor's degree in computer science, biomedical engineering, electrical engineering, medical physics, neuroscience, or a related quantitative field, or equivalent practical experience. Required.
• Doctoral degree, or master's degree with equivalent practical experience, in one of those fields. Required.
• At least five years in medical imaging engineering, scientific software development, machine learning engineering, or related fields, including relevant professional or research experience such as postdoctoral research. Required. Eight or more years preferred.
• Substantial hands-on experience with medical imaging, preferably structural brain MRI. Required.
• Experience translating research software into production systems or commercial medical software. Preferred.
• Experience mentoring engineers or providing technical leadership within multidisciplinary teams. Preferred.

Required skills

• Advanced Python programming and demonstrated experience developing production-quality scientific software.
• Strong understanding of DICOM, NIfTI, imaging metadata, spatial transformations, and medical image processing workflows.
• Designing and implementing image preprocessing, registration, segmentation, or quantitative imaging pipelines.
• Job orchestration or async pipelines, such as Prefect, Nextflow, AWS Batch, or task queues generally.
• Strong experience with PyTorch, TensorFlow, or comparable ML frameworks.
• Integrating and optimizing deep learning inference workflows.
• Strong understanding of software testing, reproducibility, versioning, and maintainable system design.
• Linux, Docker, and containerized computational workflows.
• Version control such as Git, and CI/CD systems.
• Deep experience with AWS or other cloud providers, and infrastructure as code such as Terraform.
• Demonstrated ability to independently design, implement, and troubleshoot complex technical systems.
• Ability to evaluate technical trade-offs, communicate design decisions, and collaborate across scientific and engineering disciplines.
• Strong written and verbal communication, including clear asynchronous updates for a distributed team.
• Critical thinking and creative problem solving with structured and unstructured information.
• Strong organizational and project management skills, with the ability to manage priorities across multiple teams.
• Demonstrated ability to learn new technical skills and domain knowledge quickly.

Preferred skills

• Neuroimaging software such as FreeSurfer, FastSurfer, FSL, ANTs, SynthSeg, nnU-Net, or similar tools.
• pydicom, nibabel, SimpleITK, MONAI, or related imaging libraries.
• Structural MRI preprocessing, brain segmentation, morphometry, cortical or subcortical analysis, or volumetric quantification.
• Designing automated QC and failure-handling approaches for heterogeneous clinical imaging datasets.
• Validating imaging algorithms across scanner vendors, acquisition protocols, and patient populations.
• Normative modeling, neuroanatomical reference distributions, or quantitative imaging biomarkers.
• Optimizing GPU inference and large-scale image processing workloads.
• Distributed computing or workflow orchestration tools such as Nextflow, Snakemake, or Prefect.
• Supporting medical software verification, validation, or FDA-regulated software development, for example IEC 62304 and ISO 14971.
• Medical imaging de-identification, healthcare data security, and clinical data governance.

Remote work environment

This is a fully remote position. While performing the duties of this job, the employee is expected to:

• Maintain a private, secure workspace and a reliable high-speed internet connection suitable for video meetings and handling confidential data.
• Be available for collaboration during core hours of 11:00 a.m. to 3:00 p.m. Eastern Time and for scheduled team meetings.
• Use company-issued or company-approved equipment and follow company security, device, and data handling policies.
• Travel occasionally, up to 5%, for team gatherings, conferences, or partner meetings.

Compensation and benefits

The anticipated salary range for this position is $150,000 to $190,000 per year. Final compensation will include equity, and will collectively be determined based on level of experience, skills, and qualifications. Centile Bio offers medical, dental, and vision coverage, a 401(k) plan, paid time off, and travel and supply stipends as necessary.

Equal opportunity statement

Centile Bioscience Inc. is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. Centile Bio will provide reasonable accommodations to qualified applicants and employees with disabilities. To request an accommodation during the hiring process, contact careers@centile.bio.

This job description summarizes the general nature and level of work performed. It is not an exhaustive list of all duties, and responsibilities may change as business needs evolve.