# Software Engineer, Privacy & Data Governance at Thinking Machines

- Company: Thinking Machines
- What the company does: Connectionism: Research Blog by Thinking Machines Lab. Backed by a16z, Accel and GV.
- Company website: https://thinkingmachines.ai/
- Type: Startups (AI role)
- Level: Mid level
- Location: San Francisco
- Work setup: On-site
- Pay: $300K to $350K base salary per year (USD)
- Posted: 2026-10-27
- Apply by: 2026-12-11
- Apply: https://jobs.ashbyhq.com/ThinkingMachines/d6098644-7904-4423-9330-a1b7f5767fbc?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/thinking-machines-software-engineer-privacy-and-data-governance/

## About the role

We're looking for an engineer to help manage how data is handled across Thinking Machines: what we collect and acquire, where it is stored, who and what systems can access it, how long we keep it, and how it's used in training, evaluation, and products. You'll help build the systems that let us protect privacy and make definitive statements about our practices from data inventory and classification through access and purpose controls to retention, deletion, and audit. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- Built and shipped at least one production privacy or data governance system (retention/deletion pipeline, policy evaluation engine, data cataloging and/or lineage system, consent system, or similar) and owned it through to operation, not just design
- Written and operated production code in Python or a comparable language, evidenced by a system you can walk through in detail: what it does, how it fails, how you debugged it
- Direct experience with enforcing privacy or governing data in an AI/ML data pipeline (training data, fine-tuning, inference, or evaluation) and can describe a specific privacy risk you identified or mitigated in one of these systems
- Has chosen pragmatic controls over ideal ones on real systems, and can describe what was shipped as a result
- Has written a technical requirement or control directly from a legal or policy obligation (GDPR, CCPA, or similar), and can name the obligation and the control
- Experience at an AI lab or with ML infrastructure: training data curation, multi-tenant fine-tuning platforms, or inference systems that handle user data

Tags: Security & IT

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/thinking-machines-software-engineer-privacy-and-data-governance/