Customer Service Domain Expert

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L

Job Summary

We are seeking detail-oriented LLM Trainers with experience in the Utilities industry to support the development, evaluation, and improvement of large language model outputs. The role involves creating and reviewing training data, validating model responses for utility-related use cases, and preparing visual or multimedia content using tools such as Clipchamp, Microsoft Photos, Paint, and GIMP. The ideal candidate has strong domain knowledge in utilities and a sharp eye for language quality, accuracy, and data presentation.

Key Responsibilities

• Create, review, and refine prompts, responses, annotations, and gold-standard datasets.
• Assess AI-generated content for accuracy, clarity, compliance, tone, and relevance to utility operations.
• Label, categorize, and curate text, image, and multimodal datasets for model training.
• Use Clipchamp to edit short video content, walkthroughs, voiceovers, or training clips where needed.
• Use Photos, Paint, and GIMP to crop, highlight, redact, annotate, or enhance images/screenshots for training and documentation purposes.
• Support preparation of training assets involving diagrams, service workflows, utility equipment images, forms, and customer communication examples.
• Identify hallucinations, factual inconsistencies, unsafe outputs, and domain-specific errors in model responses.
• Work closely with AI teams, data annotators, QA teams, and utility subject matter experts to improve model behavior.
• Document feedback trends, common error patterns, and recommendations for model improvement.
• Maintain data confidentiality and follow internal quality and compliance standards.

Offer Details:

• Commitments Required: at least 4 hours per day and minimum 30 hours per week with 4 hours of overlap with PST. 
• Engagement type: Contractor
• Engagement Length: 4 weeks

Evaluation Process -

• Shortlisted candidates will be sent a Job Interest Form.
• After the profile review, an assessment will be shared, which must be completed within 48 hours
• Based on the assessment outcomes, shortlisted candidates will be contacted to discuss the pre‑onboarding requirements.ent..