Machine Learning Engineer
Core
Building next-gen AI agent infrastructure on top of Postgres, including serving, evaluation, red-teaming, and continuous improvement for governance models.
Role type
Senior Machine Learning Engineer (AI Infrastructure)
Builds
AI agent infrastructure components (Agent Hub, Memory layer, MCP, governance controls) and production ML serving systems.
Domain
Enterprise Data & AI, PostgreSQL ecosystem, LLMs/Agentic Systems
Deliverable
production ML models
Required skills
Machine Learning software engineering, LLM-based or agentic systems development, low-latency ML serving, quantization/distillation, evaluation pipeline design, model registry management, red-team/adversarial testing, drift monitoring, shadow deployment, SQL, PostgreSQL
Preferred skills
Auto-retraining loops from production telemetry, Model Context Protocol (MCP), tool registries, agent orchestration patterns, Postgres extension development (C/Rust)
Technologies
Postgres, LLMs, Python, C, Rust, MCP
Responsibilities
Design and implement low-latency serving pipelines and evaluation frameworks for AI agents. Build red-team harnesses with CI-gated regression suites for security and governance. Develop self-improvement loops including continuous retraining and dataset curation. Monitor model drift and manage shadow deployments.
Seniority
Senior, hands-on IC
