ABOUT THE ROLEThis role sits at the intersection of frontier AI systems, high-quality data, and core product requirements. You will own the full data stack, from data creation, scraping, and synthesis, to managing an annotation workforce, to data cleaning, processing, evaluation, and analysis, applying sharp linguistic judgment throughout. You will play a critical role in driving modeling innovation, working closely with researchers, ML engineers, and product managers to ensure our AI systems sound natural, humanlike, and aligned with human preferences.
KEY RESPONSIBILITIES- Define requirements and own the end-to-end pipeline for creating high-quality datasets for voice agent use cases, across both text and audio modalities.
- Engineer web-scale data pipelines and apply synthetic generation techniques to produce high-quality training and evaluation data.
- Coordinate and manage a human annotation workforce: author guidelines, define quality targets, and QA annotator output.
- Build data processing and cleaning pipelines that align datasets to production needs, balancing coverage across use cases, languages, and domains.
- Analyze production logs, curated datasets, and other sources to surface failure patterns and identify high-leverage areas for targeted data collection.
- Apply your linguistic taste to judge which outputs are more natural, conversational, and humanlike, and produce preference data that encodes that judgment.
- Partner with researchers and engineers to drive each modeling iteration.
REQUIREMENTS- 2+ years of experience in computational linguistics, language data processing, or a similar field, including hands-on work with large-scale text and audio datasets.
- Highly technical: fluent at writing scripts for data processing and at leveraging models for synthetic data generation.
- Native-level command of English, with the confidence to make opinionated linguistic calls about what sounds natural in voice agent conversations.
YOU MIGHT THRIVE IF YOU- A strong applied ML background in language or audio modeling - ideally having contributed to the data pipelines behind a well-known audio or language model.
- A PhD in Computational Linguistics or an equivalent field with computational emphasis.
- Experience managing human annotation and evaluation teams.
- Excitement for building scalable systems that bridge research and production.
JOB DETAILS- Cash: 200k - 290k
- Equity: Equity Provided
- Location: Redwood City, CA, US
- US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT).
OTHER BENEFITS- 100% coverage for medical, dental, and vision insurance
- $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks
- $200/month wellness reimbursement (gym, fitness classes, etc.)
- $300/month commuter reimbursement (gas, Caltrain, etc.)
- $75/month phone bill reimbursement
- $50/month internet reimbursement
COMPENSATION PHILOSOPHY- Best Offer Upfront: Choose from three cash-equity balance options; no negotiation needed.
- Top 1% Talent: Above-market pay (top 5 percentile) to attract exceptional builders.
- High Ownership: Small teams, >$1M revenue/employee, and significant equity.
- Performance-Based: Offers tied to interview performance, not experience or past salaries.
INTERVIEW PROCESS:- Talent Screen (15min): chat with our recruiter to get a better sense of the role, the team, and what it's like to work here.
- Technical Interview (45 min): practical coding for data processing (scraping, cleaning, analysis)
- Technical Interview (45 min): linguistic judgement and preference alignment
- Onsite/Virtual Interviews (2 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:
- Dataset problem mining and fixing
- Background deep dive + behavior
