1 month ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Design and build systems for synthetic data generation, data processing, anonymization, and PII removal for frontier model training.
- Translate research, partner, and compliance needs into hypotheses, experiments, evaluation plans, and production implementations.
- Build data-processing pipelines, evaluation frameworks, benchmarks, and quality-control systems.
- Prototype, evaluate, interpret results, and incorporate learnings into subsequent systems or products.
- Partner with researchers, domain experts, customers, and legal or compliance teams to balance data utility and responsible handling.
- Productize repeatable patterns into reusable software and platforms.
- Raise engineering standards through technical judgment, communication, code quality, and mentorship.
Requirements
- 2–10 years of recent demonstrated experience in synthetic or LLM-generated data, post-training and model evaluation, privacy engineering, or large-scale data anonymization/de-identification.
- Hands-on individual contributor experience; this is not a team-lead or engineering-management role.
- Strong Python skills and experience writing clean, efficient, scalable software for large, messy datasets.
- Ability to reason about data quality, risk, and utility; form hypotheses, select metrics, diagnose failures, and distinguish signal from noise.
- Experience designing systems and making tradeoffs involving quality, scale, reliability, and reuse.
- Comfort working with substantial ownership in an ambiguous, fast-moving environment.
- Collaborative communication skills and ability to work with researchers, engineers, domain experts, and customers.
- Preferred experience includes large-scale synthetic or LLM-generated data pipelines, relational or graph-structured data anonymization, LLM or agent benchmarks, annotation systems, data-quality frameworks, reinforcement learning, alignment, model behavior, synthetic data, human-in-the-loop systems, regulated or high-sensitivity data, privacy auditing, published research, open-source contributions, or productizing research into reusable platforms.
Benefits
- Bangalore-based role with an early technical organization and substantial influence over roadmap, standards, and culture.
- Generous equity grant with four-year vesting.
- Housing bonus during the first year.
- Performance bonus opportunity.
- Medical insurance coverage.
- Food credit for each in-person workday.
- Opportunity to work with frontier AI labs, researchers, and domain experts on durable AI infrastructure.
Tech Stack
Categories
Data EngineeringML 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.