Technical Interviewer – Data & ML Platform

🔥 44 minutes ago

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Intetics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1995

🤖 Artificial Intelligence

🏢 Enterprise

Artificial Intelligence • Software Development • Enterprise

Intetics is an innovative company providing custom software development services, specializing in AI and machine learning solutions. They offer Remote In-Sourcing® to build expert teams for software engineering and data processing projects, along with advanced tools like TETRA™ for software quality assessment. Intetics aims to empower businesses by leveraging high-quality data and integrating modern technologies across various industries, including healthcare, finance, and more.

📋 Description

• 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 • Review take-home tasks or architectural diagrams if applicable • Provide clear, structured written feedback with a hire / no-hire recommendation

🎯 Requirements

• Hands-on experience designing and operating large-scale data / ML platforms • Evaluate implementation-level skills and system-level decision-making • Experience with end-to-end data platforms spanning on-prem infrastructure and AWS • Assess architectural decisions for scalability, fault tolerance, cost optimization, and data lineage • Design systems that are FDA-ready by design • Familiarity with DICOM, PACS workflows, and tools like Orthanc • Assess ingestion and QC strategies for CT imaging, Video and C-Arm data, and Radiology reports • Understanding of data validation, normalization, and failure handling in clinical pipelines • Hands-on experience with AWS Batch, preferably with Spot instances • Evaluate knowledge of job orchestration, cost-aware scaling, idempotency, retries, and large-scale batch QC • General AWS proficiency (S3, IAM, networking) • Practical experience with ClearML or comparable tools • Understand dataset lineage and provenance, experiment reproducibility, and artifact tracking • Experience with Lance or similar high-performance data access layers • Evaluate fast data loading for training, incremental dataset updates, and decoupling raw media • Strong understanding of PostgreSQL services for metadata, labels, and predictions • Assess database schema design for traceability and auditability • Familiarity with OpenSearch (text/vector) • Experience integrating labeling platforms (Encord preferred) • Evaluate understanding of RBAC and access control, QC workflows, audit trails, and label ingestion • Solid understanding of 21 CFR Part 11 expectations • Experience working with HIPAA / PHI-regulated data • Identify compliance gaps in proposed architectures • Participate in technical interviews focusing on real production and regulatory challenges • Ask scenario-based questions to evaluate experience and risk awareness • Review take-home tasks or architectural diagrams • Provide clear written feedback with a hire / no-hire recommendation