(Data & ML Platform) - Technical Interviewer

Intetics; United States; On-site; USD 100,000 - 150,000; Full time

Job summary

A leading American technology company is looking for Technical Interviewers to evaluate candidates for data engineering roles. The ideal candidates should have significant experience with large-scale data platforms, particularly in regulated environments like healthcare. Responsibilities include conducting technical interviews, providing structured feedback, and ensuring compliance with standards. Familiarity with tools such as AWS Batch, ClearML, and PostgreSQL is crucial. Previous experience in medical imaging is strongly preferred.

Qualifications

• Hands-on experience designing large-scale, FDA-compliant data/ML platforms.
• Strong understanding of regulatory compliance, especially in health care.
• Experience evaluating the impact of architectural decisions.

Responsibilities

• Participate in technical interviews focusing on system design.
• Ask scenario-based questions related to real production challenges.
• Provide structured feedback and hire/no-hire recommendations.

Skills

Experience building large-scale data platforms

Hands-on experience with AWS Batch

Strong familiarity with DICOM and PACS

Understanding of 21 CFR Part 11 compliance

Ability to evaluate technical skills

Tools

ClearML

PostgreSQL

OpenSearch

Encord

Lance

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.