19 hours ago
Base Salary
$200k - $350k/yr
Responsibilities
- Design and build systems for synthetic data generation, data quality, scale, safety, and PII removal.
- Translate research, partner, and compliance needs into hypotheses, experiments, evaluation plans, and production implementations.
- Build data-processing pipelines, evaluation frameworks, benchmarks, annotation or quality-control systems, and reusable platforms.
- Run rapid iteration loops by prototyping, evaluating results, diagnosing failures, and improving systems.
- Partner with researchers, domain experts, customers, and legal or compliance stakeholders to handle data responsibly.
- Productize repeatable patterns from engagements into durable software and platforms.
- Contribute to technical standards, design quality, communication, code quality, and mentorship.
Requirements
- 2–10 years of recent, demonstrated experience in synthetic or LLM-generated data, post-training or model evaluation, privacy engineering, or data anonymization/de-identification at scale.
- Hands-on individual contributor experience; this is not a team-lead or engineering-management role.
- Strong Python skills and the ability to build clean, efficient, scalable software for large, messy datasets.
- Ability to reason about data quality, risk, utility, metrics, hypotheses, and signal versus noise.
- Experience designing systems and making tradeoffs involving quality, scale, reliability, and reuse.
- Comfort working with substantial ownership in an ambiguous, fast-moving environment.
- Strong collaborative communication with researchers, engineers, domain experts, and customers.
- Preferred experience includes large-scale synthetic or LLM-generated data pipelines, de-identification or anonymization systems, LLM or agent benchmarks, annotation systems, data-quality frameworks, reinforcement learning, alignment, model behavior, human-in-the-loop systems, regulated or sensitive data, privacy auditing, published research, open-source contributions, technical leadership, or research productization.
Benefits
- Equity in a fast-growing company.
- 401(k) match, competitive compensation, and financial coaching.
- Paid parental leave, fertility benefits, and parental coaching.
- Medical, dental, vision, mental health support, and a $500 wellness stipend.
- $2,000 learning stipend and ongoing professional development.
- Commuting support, free lunch, and gym access at the San Francisco office.
- Flexible PTO, 15 holidays, and 2 flex days.
- Team outings and referral bonuses.
- Full-time US employee benefits are stated; San Francisco and Mountain View are preferred, with exceptional candidates considered in other locations including London, Canada, and Bangalore.
Tech Stack
Categories
Data Engineering
About Handshake
Handshake builds a career network and recruiting platform that connects college students and recent grads with employers, sold as SaaS to universities and subscriptions/solutions to employers. Founded in 2014 and headquartered in San Francisco, it serves 1,600+ educational institutions and over 1 million employers. The company also operates Handshake AI, which partners with frontier AI labs on human data collection and evaluations for model training and post-training workflows.