# Staff ML Engineer

**Company:** [Docker](https://hotfix.jobs/companies/docker)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $205k – $330k/yr
**Experience:** 8+ years
**Skills:** Machine Learning, LLMs, Prompt Engineering, Fine-Tuning, Retrieval, Guardrails, Agent Frameworks, Data Pipelines, Model Serving, Evaluation, Backend Engineering, Infrastructure
**Posted:** 2026-06-12

> Founding Staff ML Engineer building production ML systems for governance, security, and agentic platform capabilities at Docker. Owns architecture, data pipelines, evaluation, and model lifecycle while mentoring the growing team.

## Job Description

## Responsibilities
- Design, train, evaluate, and ship ML systems that power governance and security capabilities, starting with problems like prompt injection detection, behavioral anomaly detection, trust scoring, and policy recommendations.
- Build the supporting infrastructure: data pipelines, feature stores, model serving, evaluation harnesses, and the feedback loops that make iteration fast.
- Make pragmatic build-vs-buy calls. Use frontier models, off-the-shelf tooling, and managed services to move quickly; invest in custom systems where they create durable advantage.
- Set technical direction for the team's ML work. Own the architecture, evaluation methodology, model lifecycle, and the bar for shipping.
- Help recruit, mentor, and shape the team as it grows.
- Participate in a 24/7 on-call rotation for the Agentic Platform.

## Requirements
- 5+ years of deep applied ML/AI expertise with a track record of shipping production systems.
- Experience in fraud, abuse, safety, security, or trust domains, where adversarial dynamics, imbalanced data, and high-stakes decisions is valuable.
- 8+ years of professional, hands-on, full-time software engineering experience in backend, infrastructure, or platform engineering.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- You've built and owned the systems around ML models, i.e. data pipelines, serving, evaluation, monitoring etc. and have shipped customer-facing products end to end.
- You use modern AI tools fluently in your day-to-day work and have a sharp instinct for when frontier models can replace traditional ML, when they can't, and when to combine the two.
- Experience with LLM-based systems in production - evaluation, prompt engineering, fine-tuning, retrieval, guardrails, agent frameworks.
- Familiarity with the agent / MCP ecosystem.
- Energized by an early-stage effort where the roadmap is being written as the work happens, and you make crisp decisions with incomplete information.
- Collaborative and low-ego. You work well across teams, write clearly, and bring others along.

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**Apply:** https://hotfix.jobs/jobs/7b810302-cdbe-4d85-ade1-9800a7b15356
**Canonical:** https://hotfix.jobs/jobs/7b810302-cdbe-4d85-ade1-9800a7b15356