Machine Learning Engineer - Governance ML Platform

Role Overview

This opportunity is for a Machine Learning Engineer focused on developing robust production-level machine learning infrastructure centered on AI governance and trust. The position is fully remote within the EMEA region, with a key focus on next-generation AI agent capabilities using PostgreSQL.

Key Responsibilities

• Manage the ML infrastructure supporting governance models, encompassing model serving, evaluation, red-teaming, monitoring, and continual enhancement.
• Create and sustain low-latency model serving architectures and evaluation pipelines suitable for production workloads.
• Handle model registries and ancillary infrastructure to ensure dependable lifecycle management of models.
• Convert research and experimental ML models into production environments, employing optimizations such as quantization and distillation for faster inference.
• Implement drift-monitoring mechanisms and shadow deployments to detect behavioral changes and validate updated model versions safely.
• Develop pipelines to convert production telemetry and audit data into inputs for model retraining and enhancement.
• Design and maintain adversarial red-team testing infrastructure including orchestrated attacks, scorecards, regression testing, and continuous integration-based quality control.
• Set up continuous self-improvement workflows involving dataset curation, retraining, validation, and managed model rollouts.
• Install proper safeguards and deployment protocols to support secure and auditable ML operations.
• Collaborate with engineering and AI teams to advance infrastructure supporting AI agents, governance, trust, and retrieval systems.
• Promote a quality-focused engineering culture encompassing thorough documentation, testing, monitoring, and ongoing improvements.

Candidate Requirements

• Between 4 and 7 years of applied experience in machine learning software engineering, especially with large language models (LLMs) or agentic systems.
• Proficient in serving ML models in production with expertise in low-latency inference, quantization, and model distillation techniques.
• Experience creating evaluation pipelines and managing model registries effectively.
• Background in designing adversarial frameworks, including regression testing and CI-gated workflows for red-team operations.
• Practical knowledge of model drift monitoring methods and shadow deployment implementation.
• Strong command of SQL and well-versed with PostgreSQL database systems.
• Experience operating in security-conscious or compliance-regulated environments with a security-first approach.
• Robust software engineering abilities to transition ML innovations from experimental to stable production solutions.
• Capability to architect scalable infrastructure and reliable continuous assessment and improvement processes.
• Excellent communication and teamwork skills within distributed and cross-functional engineering groups.
• Bonus points for experience automating retraining through production telemetry or audit data integration.
• Familiarity with Model Context Protocol (MCP), tool registries, and AI agent orchestration patterns is advantageous.
• Experience contributing to PostgreSQL extensions developed in C or Rust, or involvement in the PostgreSQL community will be considered a plus.

Benefits & Working Conditions

• Fully remote work opportunity across the EMEA region.
• Chance to engage with cutting-edge AI agent infrastructure and ML governance technologies.
• Direct responsibility over production ML systems covering serving, security testing, evaluation, and continuous refinement.
• A unique position at the intersection of machine learning, AI agents, PostgreSQL, security, and enterprise technology.
• Access to health and wellness resources, including the CuraLinc program.
• Wellness Fridays available through the end of 2026.
• Additional region-specific benefits depending on your location.
• A remote-first culture fostering collaboration within a global engineering team.
• Opportunity to help develop secure, reliable, and enterprise-grade AI technologies.