ML Platform Engineer: Governance & Trust (Remote)

Jobgether SRL; Schweiz; Remote; CHF 120,000 - 180,000; Full time

Benefits offered by this job

100% remote work in the EMEA region

Hands-on ownership of production ML‑in

Wellness Fridays

Job summary

A partner company in Switzerland is seeking a Machine Learning Engineer to build production-grade ML infrastructure for AI governance and trust. The role is fully remote within the EMEA region and focuses on model serving, evaluation, monitoring, red-teaming, and continuous improvement.

You will work on security-sensitive systems with emphasis on reliability, traceability, and responsible deployment, turning research into robust production systems around PostgreSQL-powered components.

Qualifications

• 4–7 years of professional experience in machine learning software engineering.
• Hands-on experience building LLM-based or agentic systems.
• Strong production experience with ML model serving, low-latency inference, quantization, and distillation.
• Proven experience building evaluation pipelines and working with model registries.
• Experience designing red-team or adversarial testing frameworks with CI-gated workflows.
• Practical experience with model drift monitoring and shadow deployment strategies.
• Strong SQL skills and solid working knowledge of PostgreSQL.
• Security-first mindset in audited or security-conscious environments.
• Strong software engineering and problem-solving skills for production deployment.
• Ability to design scalable infrastructure for model evaluation and monitoring.

Responsibilities

• Own the ML infrastructure for governance models, including serving, evaluation, monitoring, red-teaming, and continuous improvement.
• Build low-latency model-serving systems and evaluation pipelines for production workloads.
• Develop and manage model registries and lifecycle infrastructure.
• Translate research models into production with optimization techniques like quantization and distillation.
• Create drift-monitoring and shadow-deployment capabilities to validate new versions safely.
• Develop telemetry-to-training pipelines from production signals and audit data.
• Design red-team testing infrastructure, scorecards, regression suites, and CI-based gates.
• Establish continuous self-improvement workflows for data curation, retraining, and rollout.
• Implement safeguards and deployment controls for auditable ML operations.
• Collaborate across engineering teams on AI agents, governance, and retrieval capabilities.
• Contribute to a high-quality engineering culture with documentation, testing, and monitoring.

Skills

ML model serving

Low-latency inference

PostgreSQL

SQL

Model drift monitoring

Red-team / adversarial testing

CI/CD

Security/compliance

Distributed engineering

Python

C/U Rust PostgreSQL extensions

Tools

Docker

Git

Job description

A partner company in Switzerland is seeking a Machine Learning Engineer to build production-grade ML infrastructure for AI governance and trust. The role is fully remote within the EMEA region and focuses on model serving, evaluation, monitoring, red-teaming, and continuous improvement.

You will work on security-sensitive systems with emphasis on reliability, traceability, and responsible deployment, turning research into robust production systems around PostgreSQL-powered components.