Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations
Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data
Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance
Configure and build custom applications and off-platform solutions for non-standard or specialized client requirements
Define production specifications and workflows, securing technical alignment with client teams to enable seamless go-live transitions
Provide ongoing technical support to Delivery Managers, addressing complex questions, resolving technical blockers, and supporting customer rebuttals
Maintain specification consistency and alignment across customer and internal teams throughout the engagement lifecycle
Identify and document workflow best practices and automation opportunities, collaborating with DaaS Engineering to continuously improve delivery capabilities
Maintain solution leaderboards and execute custom model benchmarking on existing datasets to demonstrate technical capabilities
Drive continuous improvement of technical assets, evaluation frameworks, and delivery processes to enhance speed, quality, and scalability

4+ years of experience in data science, engineering, or solution development roles. Strong practical experience with Python and SQL data tooling required
Familiarity with ML and LLM-based solutions, applying ML techniques in production contexts, and validation and evaluation of ML and LLM-based
Experience integrating systems via API

Forward Deployed Engineer – Data-as-a-Service

Key skills