Technical Solutions Architect, Evals & Fine-Tuning

Scope of the Role

Innodata partners with leading foundation model labs, hyperscalers, and enterprise AI teams to build the data, evaluation, and post-training systems that make modern LLMs trustworthy and production-ready.

As a Technical Solutions Architect for Evals & Fine-Tuning, you are the technical face of Innodata to our most demanding customers. You sit at the intersection of client AI/ML teams, our research scientists and ML engineers, our subject-matter expert workforce, and our platform teams. You translate ambiguous customer goals — “improve factuality on long-context legal QA,” “build a safety eval suite for our next model release,” “design a DPO pipeline for our coding assistant” — into concrete, scoped, deliverable engagements.

This is a senior individual-contributor role for someone who has done the work: built fine-tuning pipelines, designed eval harnesses, argued with stakeholders about benchmark validity, and earned credibility with sophisticated ML buyers.

What You’ll Own

• Lead technical discovery with prospective and existing customers — foundation model labs, frontier AI teams, and large enterprises — to understand model objectives, gaps, and constraints.
• Design end-to-end solutions across the post-training stack: SFT data curation, preference data collection for RLHF/DPO, golden datasets, custom benchmarks, LLM-as-judge pipelines, human-in-the-loop evaluation, red teaming, and multimodal eval (text, image, audio, video, long-context).
• Architect engagements that combine Innodata’s platforms (GenAI Test & Evaluation Platform, Annotation Platform, GenAI Workbench) with our global SME workforce across 85+ languages and domains.