---
title: 'Member of Technical Staff, AI Engineering (India) at Handshake'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ai-engineering-india-handshake-india-ntg51nad631j'
type: 'job'
last_seen: '2026-10-14'
---

# Member of Technical Staff, AI Engineering (India) at Handshake

- **Company:** [Handshake](https://feeny.ai/companies/handshake)
- **Location:** India
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-09
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.ashbyhq.com/handshake/4870c024-f6b8-4c2d-a5cb-e94f6c8f94a9

## Job description

## About Handshake

Handshake's mission is to organize expert human knowledge to advance the AI economy. Handshake AI works directly with frontier labs on their most consequential data, evaluation, and post-training challenges, building the systems that turn expert human knowledge into the data and evaluations that make frontier models better. You will work alongside engineers, researchers, operators, and builders from organizations including Scale AI, Meta, Google, Amazon, xAI, Notion, and Palantir—and help build the systems that make expert human knowledge useful for advancing AI.

## About Handshake Labs

Handshake Labs is building external AI products, research platforms, and customer-facing AI systems. We are evolving work that is often custom-built for an individual partner into reusable products and platforms that improve with every deployment. Our work spans the full post-training loop: designing evaluations and training environments, building high-quality data and feedback systems, running experiments, and turning what works into durable infrastructure. For example, we are developing agents that can analyze long, complex coding-agent sessions in days rather than weeks—with expert review and calibration built into the system.

## The Role

We are hiring a Member of Technical Staff to help build the data systems that make frontier model training possible. The data Handshake builds for and acquires on behalf of labs is getting more complex and more sensitive, and this role is responsible for improving how we generate, process, and prepare that data—whether that means building higher-quality synthetic and LLM-generated training data, or making acquired third-party data safe to use by removing personal information while preserving the structure that makes it valuable. You will partner with researchers, domain experts, legal/compliance stakeholders, and customers to turn ambiguous data questions—about generation, quality, evaluation, or privacy—into experiments, pipelines, and durable products. Early members of the team will have unusual influence over our technical direction, standards, and culture. Location: Bangalore

## What you’ll do

- Design and build systems that improve the quality, scale, and safety of the data Handshake generates and acquires for frontier model training—spanning synthetic data generation and data anonymization/PII removal.
- Translate ambiguous research, partner, or compliance needs into clear hypotheses, experiments, evaluation plans, and production-quality implementations.
- Build and improve data-processing pipelines, evaluation frameworks, benchmarks, and quality-control systems, whether the goal is generating higher-signal synthetic data or verifying that sensitive data has been properly de-identified.
- Run fast, rigorous iteration loops: prototype, evaluate, interpret results, and turn learnings into the next system or product.
- Partner directly with researchers, domain experts, and—where relevant—legal and compliance teams to ensure data is both high-utility and responsibly handled.
- Identify repeatable patterns across engagements and productize them into reusable software and platforms.
- Raise the technical bar through strong design judgment, clear communication, code quality, and mentorship.

## What we’re looking for

- 2–10 years of recent, demonstrated experience in one or more of: synthetic/LLM-generated data, post-training and model-evaluation work, privacy engineering, or data anonymization/de-identification at scale.
- A hands-on individual contributor track record—this is not a team-lead or engineering-management role.
- Strong Python skills and the ability to write clean, efficient, scalable software for large, messy, real-world datasets.
- Sound judgment for reasoning about data quality, risk, and utility—forming hypotheses, choosing meaningful metrics, diagnosing failures, and distinguishing signal from noise.
- Experience designing systems—not only implementing specifications—including tradeoffs around quality, scale, reliability, and reuse.
- Comfort operating in an ambiguous, fast-moving environment with substantial ownership.
- Collaborative, low-ego communication and the ability to work effectively with researchers, engineers, domain experts, and customers.

Especially compelling experience

- Building or operating large-scale synthetic or LLM-generated data pipelines for model training.
- Building or operating large-scale data de-identification or anonymization systems, ideally involving relational or graph-structured data, with experience preserving referential/relationship integrity after anonymization.
- Developing LLM/agent benchmarks, evaluation methodologies, annotation systems, or data-quality frameworks.
- Research or applied work on reinforcement learning, alignment, model behavior, synthetic data, or human-in-the-loop systems.
- Prior work in a regulated or high-sensitivity data environment (healthcare, finance, HR/people data, government), or experience with re-identification risk assessment and privacy auditing.
- Published research, meaningful open-source contributions, or evidence of technical leadership in ML systems, data engineering, or AI research.
- Experience productizing research or repeated customer work into robust, reusable platforms.

## Why join

- Work on problems at the center of how frontier AI systems improve, alongside leading labs and domain experts.
- Help build an early technical organization where your work shapes the roadmap, standards, and culture.
- Move fluidly from research insight to real-world systems, with the resources and customer context to see those systems matter.
- Join a company building durable infrastructure for careers in the AI economy.

Perks:

- Generous Equity Grant vested over 4 years
- Housing Bonus: 1.3 Lakhs spread throughout the first year
- Well Defined Performance Bonus ranging between 10 - 100% of base
- Medical Insurance Coverage
- Food credit for every in person day.

## About Handshake

## Company Overview
- **One-liner**: Handshake is the career network for the AI economy, connecting job seekers with internships, full-time roles, freelance gigs, and AI training work through a three-sided marketplace.
- **Entity Type**: Private (Series F; total funding $434M across 6 rounds)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2014
- **Founders**: Garrett Lord (CEO), Ben Christensen, Scott Ringwelski

## Core Business
- **Primary industry**: Career platform / Job marketplace / AI workforce infrastructure
- **Target customers**: B2C (job seekers, from students to experienced professionals) and B2B (employers including 100% of Fortune 500 and all foundational AI labs; also educational institutions)
- **Mission**: Expand access and improve outcomes for job seekers, helping the workforce stay ahead in the AI economy.

## Products & Services
- **Handshake Core Platform**: A three-sided marketplace connecting 25 million knowledge workers, 1,600+ schools, and 1 million employers. Features dynamic profiles, intelligent job matching, and interactive skill-building.
- **Handshake AI Enterprise**: AI-powered tools for employers and job seekers, including AI-driven matching, safety features, and pay management.
- **AI Trainer Gigs**: Paid, flexible, remote work for individuals to train and evaluate AI models (e.g., AI Evaluation Specialist, up to $40/hr) – no prior AI experience required.
- **Handshake Network**: Community events, career advice, and networking for students, experts, and professionals in AI and other fields.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding $434M (6 rounds); annual revenue $56.5M (LinkedIn estimate)
- **Notable Investors/Partners**: Board includes representatives from General Catalyst, Kleiner Perkins, EQT Ventures, True Ventures, and Niantic. Strategic partners include 100% of the Fortune 500 and foundational AI labs.
- **Growth Signals**: Headcount at 5,272 employees (+708.8% YoY per LinkedIn); 1M+ companies on platform; 25M users; expansion into AI trainer gig economy; new roles in HAI (Handshake AI Enterprise) such as Applied AI Engineer, AI Platform Engineer, and Forward Deployed Engineer.

## Competitive Advantages
- **Network effects**: The only three-sided marketplace linking students, employers, and educational institutions at scale.
- **AI-first positioning**: Deep integration of AI into job matching, skill-building, and new freelance training roles – creating a unique ecosystem for the AI economy.
- **Trusted by elite institutions**: 1,600+ partner schools and every Fortune 500 company provides unparalleled reach into early-career talent.

## Strategic Focus
- **AI economy expansion**: Building the “career network for the AI economy” – expanding beyond college students to all knowledge workers, and adding AI training gigs as a new revenue and engagement stream.
- **Product innovation**: Heavy investment in Handshake AI Enterprise (HAI), including AI matching, safety, and pay infrastructure.
- **Global scaling**: Offices in San Francisco, New York, UK, and Bangalore; operating in 32 countries.

## Why Work Here
- **Culture**: Values include “Students first,” “Leave nothing to chance,” “Own the outcome,” “Invent and reinvent,” and “Olympic pace.” Emphasis on ownership, urgency, and constant evolution.
- **Remote/Hybrid policy**: Many roles are based in San Francisco or New York, but some positions (e.g., Trust & Safety Specialist, Support Specialist) are remote in the US. Recent openings show both office and remote options.
- **Benefits**: Health & wellness support, financial support, time off, modern offices with meals, snacks, and social activities. Strong focus on career growth and learning.
- **Career growth**: Rapid headcount growth suggests ample internal mobility; roles range from engineering (ML, AI, data) to customer success, partnerships, and product management.

## Sources
1. [joinhandshake.com/about](https://joinhandshake.com/about/)
2. [joinhandshake.com/careers](https://joinhandshake.com/careers/)
3. [linkedin.com/company/team-handshake](https://www.linkedin.com/company/team-handshake)
4. [joinhandshake.com](https://joinhandshake.com/)

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