(Data & ML Platform) - Technical Interviewer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 9h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 229d ago
The date the source published, not the day we noticed it (2026-01-29). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Ukraine, Armenia, Georgia, Moldova
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay £74k–98.8k/yr
Middle 50% of 12 listings that do state pay — Operations · all levels · EMEA · GBP/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 11d ago · last seen just now
The listing
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.