Data Manager — Multimodal Medical Foundation Models

SAIGroup; Bengaluru; On-site; INR 800,000 - 1,500,000; Full time

Benefits offered by this job

Competitive compensation

Access to unique medical datasets

Collaboration with leading scientists

Job summary

A leading medical AI organization in Bengaluru seeks a Data Manager to oversee data operations for 3D medical multimodal foundation models. This role involves managing extensive datasets, ensuring data quality and compliance, and collaborating with engineers and researchers to build data systems vital for advancing medical AI. The ideal candidate has a strong background in medical imaging and data management processes. This position offers a high-impact opportunity with competitive compensation and a mission-driven team.

Qualifications

• Strong experience managing large multimodal or imaging datasets, ideally medical imaging.
• Experience with distributed data systems and cloud/on-prem storage.
• Understanding of data privacy, de-identification, and compliance requirements.

Responsibilities

• Lead data operations for multimodal medical models.
• Oversee ingestion and processing of 3D medical volumes.
• Implement scalable data storage and retrieval systems.

Skills

Managing large multimodal datasets

Proficiency with DICOM/DICOMweb

Experience with ETL pipelines

Comfortable with Python and SQL

Strong communication skills

Tools

Airflow

MONAI

Job description

Data Manager — Multimodal Medical Foundation Models

About the Role

You will lead data operations for a cutting-edge research group developing3D medical multimodal foundation modelsandagentic clinical AI systems. These models rely on extremely high-quality, well-structured, and compliant datasets—including3D medical imaging volumes (MRI, CT, PET),clinical text corpora,annotations, andmultimodal metadata.

Your job is to own the end-to-end data lifecycle:acquisition, ingestion, cleaning, versioning, labeling, quality control, governance, and delivery to researchers. You are the central node ensuring our foundation model teams and medical agent teams have clean, scalable, well-documented data pipelines.

This is a pivotal foundational role—without great data, large models cannot be great.

What You Will Work On

• Oversee ingestion and processing of3D medical volumes(DICOM, NIfTI, MHA) and associated clinical texts.
• Build automated pipelines formetadata extraction,de-identification,slice/series validation, andcohort structuring.
• Manage large-scale internal datasets and external research datasets (BraTS, LiTS, MIMIC-CXR, CheXpert, MosMed, etc.).
• Implement scalabledata storage, cataloging, and retrievalsystems for multimodal training data.
• Own datasetversion control, lineage tracking, reproducibility, and dataset documentation.
• Collaborate with ML systems engineers on high-throughputdata loaders, sharding strategies, and caching mechanisms.

Annotation & Labeling Programs

• Lead medical annotation workflows with radiologists, medical students, and labeling vendors.
• Create guidelines forROI labeling,segmentation,captioning,report alignment, andcase-level curation.
• Buildsemi-automated labeling pipelinesusing model-assisted tools.

Data Quality, Compliance & Governance

• Enforce strict standards on dataquality,completeness,consistency, andbias control.
• Ensure adherence tomedical data privacy,HIPAA-equivalent frameworks, and institutional data-sharing rules.
• Manage PHI de-identification, audit logs, access control, and compliance approvals.

Collaboration with Research & Engineering

• Work closely with foundation-model researchers to understand data needs for model training.
• Partner with agentic system designers to supply structured datasets for clinical reasoning tasks.
• Collaborate with foundational engineers on data access layers, performance bottlenecks, and dataset optimization.

Why This Role Is Critical

• The foundation model relies onhigh-quality 3D and textual dataat scale.
• You shape thedata pipelinesenabling next-generation medical AI agents.
• You ensureclinical-grade governance, safety, reproducibility, and trust.
• Your systems become the backbone for research, experiments, and deployments.

For candidates motivated by the intersection of data, healthcare, and machine learning, this is a high-impact opportunity.

What We’re Looking For

• Strong experience managinglarge multimodal or imaging datasets, ideally medical imaging.
• Proficiency withDICOM/DICOMweb, NIfTI, PACS systems, and medical imaging toolkits (dicompyler, pydicom, MONAI, ITK).
• Experience withETL pipelines, distributed data systems, and cloud/on-prem storage.
• Knowledge ofmetadata standards, ontologies, and text–image linking strategies.
• Comfortable working with Python, SQL, and data tooling (Airflow, Prefect, Dagster, DBT, Delta Lake, etc.).
• Understanding ofdata privacy, de-identification, and compliance requirements in healthcare.
• Strong communication skills and the ability to coordinate between engineers, researchers, clinicians, and data partners.

Nice to Have

• Experience withvector databases, multimodal retrieval, or embedding store design.
• Familiarity with annotation tools (Labelbox, CVAT, iMerit, custom MONAI Label pipelines).
• Prior work with clinical NLP datasets or multilingual Indian medical corpora.
• Experience conductingbias audits, dataset characterization, or quality scoring at scale.
• Contributions to open datasets, benchmarks, or data documentation frameworks.

What We Offer

• Competitive compensation.
• Access to one of the most ambitiousmedical multimodal datasetsin the region.
• Collaboration with scientists building India’s first 3D multimodal medical foundation model.
• Autonomy to design data systems from the ground up.
• A mission-driven team working to transform clinical care with agentic AI.