(Data & ML Platform) - Technical Interviewer
Intetics
Posted: January 29, 2026
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Quick Summary
Design and operate large-scale data / ML platforms in medical imaging or regulated environments, with a focus on traceability, compliance, and system-level decision-making.
Required Skills
Job Description
Intetics Inc. is a leading American technology company providing custom software application development, distributed professional teams creation, software product quality assessment, and “all-things-digital” solutions, is looking for Technical Interviewers.
Expert Profile Overview
The technical expert should have hands-on experience designing and operating large-scale data / ML platforms, ideally in medical imaging or regulated environments.
They must be able to evaluate both implementation-level skills and system-level decision-making, with a strong focus on traceability, compliance, and production readiness.
Areas of Expertise Required
Data & ML Platform Architecture
• Experience building end-to-end data platforms spanning on-prem infrastructure and AWS.
• Ability to assess architectural decisions related to scalability, fault tolerance, cost optimization, and data lineage.
• Understanding of how to design systems that are FDA-ready by design, not retrofitted.
Medical Imaging & Ingestion Pipelines
• Strong familiarity with DICOM, PACS workflows, and tools such as Orthanc.
• Ability to assess ingestion and QC strategies for:
• CT imaging
• Video and C-Arm data
• Radiology reports
•
• Understanding of data validation, normalization, and failure handling in clinical pipelines.
Distributed Processing & AWS
• Hands-on experience with AWS Batch, preferably with Spot instances.
• Ability to evaluate candidate knowledge of:
• Job orchestration
• Cost-aware scaling
• Idempotency and retries
• Large-scale batch QC and inference workloads
•
• General AWS proficiency (S3, IAM, networking concepts).
Dataset Versioning & Experiment Tracking
• Practical experience with ClearML or comparable tools.
• Ability to assess:
• Dataset lineage and provenance
• Experiment reproducibility
• Artifact and metric tracking
•
• Understanding of how these capabilities support regulatory audits.
Training Data Access & Storage Optimization
• Experience with Lance or equivalent high-performance data access layers.
• Ability to evaluate candidate approaches to:
• Fast data loading for training
• Incremental dataset updates
• Decoupling raw media from derived data
•
Metadata, Labels & Search
• Strong understanding of PostgreSQL-based services for metadata, labels, and predictions.
• Ability to assess database schema design for traceability and auditability.
• Familiarity with OpenSearch (text/vector) as a plus.
Labeling Workflows
• Experience integrating labeling platforms (Encord preferred).
• Ability to evaluate candidate understanding of:
• RBAC and access control
• QC and review workflows
• Audit trails
• Algorithmic label ingestion and updates
•
Regulated Environments & Compliance
• Solid understanding of 21 CFR Part 11 expectations:
• Access control
• Audit trails
• WORM storage
• Data provenance
•
• Experience working with HIPAA / PHI-regulated data.
• Ability to identify compliance gaps in proposed architectures.
Interview Responsibilities
The technical expert will be expected to:
• Participate in technical interviews (system design + deep dive).
• Ask scenario-based questions focused on real production and regulatory challenges.
• Evaluate candidate answers for:
• Practical experience vs. theoretical knowledge
• Trade-off awareness
• Risk identification and mitigation
•
• Review take-home tasks or architectural diagrams if applicable.
• Provide clear, structured written feedback with a hire / no-hire recommendation.
Ideal Background of the Expert
• Senior / Principal Data Engineer, ML Platform Engineer, or MLOps Engineer.
• Prior experience in healthcare, medical imaging, or regulated ML systems is strongly preferred.
• Comfortable challenging candidates and defending technical decisions in front of stakeholders.