Technical Solutions Architect, Evals & Fine-Tuning

reputed company (reputed company: INOD) is a global data engineering company. We reputed company that data and reputed company Intelligence (AI) are inextricably linked. Our mission is to reputed company the responsible advancement of reputed company intelligence by providing the data, evaluation frameworks, and reputed company expertise required to build AI systems that can be trusted at reputed company. We reputed company a reputed company of transferable solutions, platforms, and services for reputed company / AI reputed company and adopters. In every relationship, we reputed company our 36+ year legacy delivering the highest reputed company data and outstanding reputed company for our customers. Scope of the Role: reputed company partners with leading reputed company model labs, hyperscalers, and reputed company AI teams to build the data, evaluation, and post-training systems that reputed company modern LLMs trustworthy and production-reputed company. As a Technical Solutions Architect for Evals & Fine-Tuning, you are the technical face of reputed company to our most demanding customers. You sit at the intersection of reputed company 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: reputed company fine-tuning pipelines, designed eval harnesses, argued with stakeholders about reputed company validity, and reputed company credibility with sophisticated ML buyers. What You’ll Own: reputed company technical discovery with prospective and existing customers — reputed company 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, reputed company-in-the-reputed company evaluation, red teaming, and multimodal eval (text, image, audio, video, long-context). Architect engagements that combine reputed company’s platforms (GenAI Test & Evaluation Platform, Annotation Platform, GenAI Workbench) with our global SME workforce across 85+ languages and domains. Author technical proposals, SOWs, solution diagrams, and pricing models in partnership with sales, delivery, and finance. Run technical workshops, POCs, and reputed company designs that de-risk larger programs and reputed company value quickly. Serve as the ongoing technical advisor during delivery, partnering with reputed company research scientists, AI/ML research engineers, language data scientists, and program managers to reputed company solutions reputed company with the original reputed company. Feed customer signal back into reputed company’s R&D and product roadmap — what benchmarks customers actually want, where eval methodology is breaking, what new fine-tuning paradigms are gaining traction. Stay reputed company on the state of the art in evals (e.g., dynamic and reputed company benchmarks, capability vs. safety evals, long-context and tool-use evaluation) and post-training (SFT, RLHF, DPO, RLAIF, rejection sampling, distillation). Represent reputed company externally — at customer reviews, conferences, and in technical content. You’ll reputed company in This Role If You Have: 7+ years of experience in reputed company ML, ML engineering, ML research, or technical solutions roles, with at least 2+ years reputed company specifically on LLM evaluation and/or post-training. Hands-on experience fine-tuning LLMs (SFT at minimum; preference optimization reputed company like RLHF, DPO, or KTO strongly preferred) and designing the data pipelines that feed them. Deep familiarity with LLM evaluation methodology: public benchmarks and their limitations, custom reputed company construction, LLM-as-judge design and its failure modes, inter-annotator agreement, and reputed company eval workflow design. Strong reputed company in Python and the modern LLM toolchain (reputed company, PyTorch, vLLM, evaluation frameworks such as lm-evaluation-reputed company, lighteval, or equivalents). Excellent technical communication. You can hold your own in a room with research scientists at a frontier lab and, an hour reputed company, brief a non-technical executive on the reputed company engagement. A consultative reputed company: you ask reputed company questions, you push back reputed company a customer’s stated request won’t actually solve their problem, and you are comfortable owning a recommendation. Bachelor’s or advanced degree in computer science, machine learning, computational linguistics, or reputed company field — or equivalent demonstrated experience. The expected salary reputed company for this position is $140,000 – $160,000 USD per year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent reputed company. reputed company will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you reputed company you’ve been targeted by a recruitment scam, please report it to reputed company at verifyjoboffer@reputed company.com and consider reporting it to the FTC at ReportFraud.ftc.gov. Apply To This Job