Machine Learning Engineer (Governance ML Platform)
E
EDBMachine learning infrastructure
Remote EMEAFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 4–7 years of professional machine learning software engineering experience
- Required Skills
- PostgreSQLSQLMachine Learning
Requirements
- Have 4–7 years of professional machine learning software engineering experience.
- Bring hands-on experience with LLM-based or agentic systems.
- Have deep production ML serving experience, including low-latency inference.
- Have experience with quantization or distillation.
- Have experience building evaluation pipelines and using model registries.
- Have experience with red-team or adversarial testing harnesses and CI-gated regression suites.
- Have experience with drift monitoring and shadow deployment.
- Be fluent with SQL and PostgreSQL.
- Bring a security-first mindset and experience in audited environments.
- Experience building auto-retraining loops from production telemetry or audit data is an edge.
- Familiarity with MCP, tool registries, and agent orchestration patterns is an edge.
- Postgres extension development in C or Rust, or contributions to the Postgres ecosystem, is an edge.
Responsibilities
- Build low-latency serving and evaluation pipelines for governance models.
- Manage model registries and production ML serving.
- Deliver inference under 50ms using quantization or distillation.
- Monitor drift and implement shadow deployments.
- Build telemetry-to-training pipelines.
- Develop red-team harnesses for attack orchestration, scorecards, and regression suites.
- Implement CI gating for red-team and regression testing.
- Create continuous retraining and dataset curation from the audit trail.
- Gate model auto-rollouts.
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