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ZeroDrift, Inc.

Principal ML Engineer

New York, New York

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hirly's read of this role

Role family
Data & ML
Seniority
Lead / management
Stated salary
$200,000 – $250,000 per year
Country
US
Work mode
Remote-friendly
First seen by hirly
3 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

  • About ZeroDrift
  • ZeroDrift is building the AI-native compliance enforcement infrastructure for enterprise communication. We
  • are the first platform that enforces compliance before an AI message is ever sent, fixing violations in real
  • time across every channel where AI speaks for the business. Everything goes out clean. Nothing dangerous
  • comes in.
  • As AI starts to communicate on behalf of entire organizations, the gap between what compliance requires
  • and what companies can actually enforce is widening fast. Every existing solution monitors after send, once
  • the risk is already out the door. ZeroDrift enforces compliance before send. Compliance enforcement did
  • not exist as a category. We created it.
  • We are backed by Andreessen Horowitz (a16z) and other world-class VCs, and built by a team from
  • Microsoft, Google, and Goldman Sachs, led by a repeat AI founder.
  • The Role
  • Compliance enforcement runs on specialized language models. They decide in real time whether a
  • communication is safe to send, and they have to be accurate, fast, and reliable, because they sit in the path
  • of live traffic.
  • Our AI research team owns the science: model behavior, training objectives, data strategy, and the quality
  • bar. You own the systems that make the science real. You will build the pipelines that train models
  • reproducibly, the evaluation infrastructure that proves they work, and the serving stack that runs them in
  • production.
  • This is a hands-on principal individual contributor role on a small, senior team. It is a systems role, not a
  • research role. The right candidate loves making ML industrial-grade.
  • What you'll do
  • Build and own the training pipelines: data preparation, reproducible fine-tuning runs, experiment
  • tracking, and release automation
  • Build the evaluation infrastructure: automated eval runs, regression gates, dashboards, and dataset
  • versioning. Research defines what good means. You build the machinery that measures it
  • Own model serving in production: low-latency inference, batching, optimization, autoscaling, and cost
  • Ship model updates safely with versioning, canarying, rollback, and drift monitoring
  • Build repeatable workflows for adapting models to new domains and customer needs
  • Turn expert labels and reviewer feedback into clean training and evaluation data
  • Set the bar for ML infrastructure as the team grows
  • What we're looking for
  • 8+ years of software engineering experience, including 4+ years building infrastructure for ML or LLM
  • systems in production
  • Hands-on depth with the modern LLM stack: PyTorch, distributed training, fine-tuning at scale (LoRA,
  • SFT), and inference engines such as vLLM or TensorRT-LLM
  • You have built eval harnesses, regression gates, or dataset pipelines, and you understand precision,
  • recall, and calibration well enough to build the right measurement around them
  • Production mindset. You have owned model serving with real latency, reliability, and cost constraints,
  • not just notebooks
  • Strong fundamentals: Python, containers, CI/CD, cloud infrastructure, observability
  • High ownership on a small team: scope your own work, ship weekly, make pragmatic build-vs-buy calls
  • You enjoy being the engineering counterpart to a research partner. Tight collaboration, clear interfaces,
  • no turf wars
  • Nice to have
  • Experience productionizing small or specialized language models
  • Experience with structured-output serving or constrained decoding in production
  • Prior work in a regulated or high-stakes domain such as fintech, healthcare, legal, or trust and safety
  • Experience deploying models into customer-controlled environments
  • Compensation and benefits
  • $200,000 to $250,000 base salary, depending on experience
  • Performance bonus and meaningful early-stage equity
  • Health, dental, and vision coverage
  • Hybrid work from our New York office
  • ZeroDrift is an equal opportunity employer. We evaluate candidates without regard to race, color, religion,
  • sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected characteristic.
Original posting on ZeroDrift, Inc.'s site ↗

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