• Lead the design and implementation of data pipelines that prepare high-quality training data for AI models. • Build data curation workflows that transform raw enterprise data into labeled, validated datasets. • Design data quality frameworks: validation, profiling, anomaly detection, lineage tracking. • Extend existing anonymized data export pipelines to support AI training workloads. • Implement synthetic data generation pipelines. • Design schema mappings across 197+ enterprise tables for feature extraction. • Collaborate with ML engineers on training data format requirements. • Establish data catalog and metadata management for AI training artifacts.

Duties: (1) conduct cable burial risk assessment utilizing advanced spatial analysis to define subsea cable protection requirements (2) perform subsea cable burial assessment through numerical modelling of cable burial tooling to assess trencher tool performance under seabed conditions (3) perform advanced geohazard assessments to deliver subsea cable routing design and risk mitigation reports (4) perform subsea cable transportation and installation strategy development including detailed assessment of cable installation by using discrete event simulation software (5) apply offshore marine engineering techniques and complete vessel and equipment suitability assessments for offshore construction projects. 100% telecommuting permitted from any location in the U.S. Requirements: U.S. Bachelors Degree (or foreign equivalent) in marine engineering or mechanical engineering and one year experience as a marine engineer. Mail Resume to American Global Maritime, c/o Eric Frank, President at 26400 Kuykendahl Rd, Suite C 180 601, The Woodlands, TX 77375.

• Design and optimize VLM prompts for document classification, text extraction, and rule validation tasks. • Build and run evaluation pipelines to measure accuracy, cost, and latency across model configurations. • Benchmark new models (Azure OpenAI, others) and recommend upgrades based on quality/cost tradeoffs. • Implement structured output extraction from LLMs using function calling, JSON mode, and Pydantic-based parsing. • Maintain and extend a Python service layer (FastAPI, queue-based workers) and a Next.js frontend. • Build scalable, fault-tolerant AI pipelines using Azure components such as App Services, Blob Storage, and queues. • Monitor, debug, and resolve production issues across AI and application layers.

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems • Own production rollouts of consumer and internally facing GenAI applications • Serve as a trusted technical advisor to customers across a variety of domains • Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally • Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap