[All remote jobs](https://jobicy.com/jobs.md)[![EDB logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/6c7d3949-221.png)](https://jobicy.com/company/edb.md)[EDB](https://jobicy.com/company/edb.md) # Machine Learning Engineer (Governance ML Platform) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/edb.md)ShareRemote from[EMEA](https://jobicy.com/job-region/emea.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceOpen levelPublished18 Oct 2026Apply before17 Nov 2026Listing views17Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. EDB is seeking an experienced Machine Learning Engineer to build governance-focused ML infrastructure for AI agents running on Postgres. The role owns low-latency model serving, evaluation pipelines, model registry capabilities, adversarial testing, and continuous improvement workflows. Key work includes quantization or distillation, drift monitoring, shadow deployments, telemetry-driven retraining, and CI-gated regression suites. Candidates need 4–7 years of ML software engineering experience, strong SQL and PostgreSQL fluency, and hands-on experience with LLM or agentic systems in production. This is a 100% remote position for candidates in EMEA. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior, highly technical production ML platform role combining LLM infrastructure, low-latency inference, security governance, evaluation systems, and adversarial testing. The engineer is expected to own critical platform capabilities and make independent architecture and rollout decisions. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$135,000US market range (per year)$115k–$170k0$187.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation was disclosed. The annual USD figures are AI-estimated market compensation for a mid-to-senior production ML engineering role with LLM infrastructure, model-serving, and governance responsibilities; yearly cadence is inferred from the full-time professional role convention. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning Engineering](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Engineering.md)[LLM Systems](https://jobicy.com/jobs?search_keywords=LLM%20Systems.md)[Agentic AI](https://jobicy.com/jobs?search_keywords=Agentic%20AI.md)[Model Serving](https://jobicy.com/jobs?search_keywords=Model%20Serving.md)[Low-Latency Inference](https://jobicy.com/jobs?search_keywords=Low-Latency%20Inference.md)[Model Evaluation](https://jobicy.com/jobs?search_keywords=Model%20Evaluation.md)[Model Registry](https://jobicy.com/jobs?search_keywords=Model%20Registry.md)[Quantization](https://jobicy.com/jobs?search_keywords=Quantization.md)[Knowledge Distillation](https://jobicy.com/jobs?search_keywords=Knowledge%20Distillation.md)[Drift Monitoring](https://jobicy.com/jobs?search_keywords=Drift%20Monitoring.md)[Shadow Deployment](https://jobicy.com/jobs?search_keywords=Shadow%20Deployment.md)[Adversarial Testing](https://jobicy.com/jobs?search_keywords=Adversarial%20Testing.md)[PostgreSQL](https://jobicy.com/jobs?search_keywords=PostgreSQL.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md) Sample interview questionsHow would you design a low-latency serving system for governance models with a sub-50 ms inference target?I would begin with a latency budget covering preprocessing, model execution, network overhead, and postprocessing. I would evaluate model quantization, distillation, batching strategy, hardware selection, caching, and co-location of dependent services, then instrument p50, p95, and p99 latency. I would also use load testing and shadow traffic before enabling production rollout. What should an evaluation pipeline for an LLM governance model include? It should include versioned datasets, representative benign and adversarial prompts, task-specific metrics, safety and policy scorecards, reproducible execution, and clear acceptance thresholds. Results should be stored with model and dataset versions in a registry so teams can compare candidates and prevent regressions through CI gates. How would you build a red-team harness for an AI agent platform? I would define attack categories such as prompt injection, data exfiltration, tool misuse, privilege escalation, jailbreaks, and unsafe retrieval behavior. The harness would orchestrate repeatable attacks, capture traces and outcomes, score policy adherence, and turn confirmed failures into versioned regression tests that block unsafe releases. How would you safely implement continuous retraining from production telemetry and audit data? I would use governed data collection with privacy controls, lineage, quality checks, and explicit labeling or review workflows. Candidate models would be evaluated offline, validated with shadow deployment, and released through gated rollout criteria with monitoring and rapid rollback. Audit trails should record the data, model version, evaluation outcomes, approvers, and release decision. How does PostgreSQL fit into an ML governance and agent infrastructure platform? PostgreSQL can provide durable storage for audit events, evaluation results, model metadata, policy configurations, and curated training data. Its SQL capabilities support traceable analysis and governance reporting, while extensions or integrations can enable retrieval, vector workflows, and close coupling between agent state and operational data. Opportunity details ## About this role. A Little About Us EDB provides a data and AI platform that enables organizations to harness the full power of Postgres for transactional, analytical, and AI workloads across any cloud, anywhere. EDB empowers enterprises to control risk, manage costs and scale efficiently for a data and AI led world. Serving more than 1,500 customers globally and as the leading contributor to the vibrant and fast-growing PostgreSQL community, EDB supports major government organizations, financial services, media and information technology companies. EDB’s data-driven solutions enable customers to modernize legacy systems and break data silos while leveraging enterprise-grade open source technologies. EDB delivers the confidence of up to 99.999% high availability with mission critical capabilities built in such as security, compliance controls, and observability. For more information, visit [www.enterprisedb.com](http://www.enterprisedb.com/) Candidate Note: This position is 100% remote EDB is building the next generation of AI agent infrastructure on top of Postgres including an Agent Hub, an Agent Memory layer, MCP, governance and trust controls, and enterprise-grade retrieval. We’re looking for an experienced Machine Learning (ML) Engineer to own the ML infrastructure spanning serving, evaluation, red-teaming, and continuous improvement for governance models. And turning Postgres into a first-class platform for AI agents. What your impact will be: * Serving & evaluations: low-latency serving, eval pipelines, model registry. * Research-to-production: <50ms inference via quantization/distillation, drift monitoring, shadow deployment, telemetry-to-training pipelines. * Red-team harness: attack orchestration, scorecards, regression suites, CI gating. * Self-improvement loop: continuous retraining, dataset curation from the audit trail, gated auto-rollout. What you will bring: * 4–7 years of professional machine learning software engineering experience, with hands-on work on LLM-based or agentic systems. * Deep production ML serving experience (low-latency inference, quantization/distillation). * Evaluation pipeline and model registry experience. * Red-team/adversarial testing harness experience (CI-gated regression suites). * Drift monitoring/shadow deployment experience. * Fluency with SQL and PostgreSQL. * Security first mindset and experience in audited environments. What will give you an edge: * Experience building auto-retraining loops from production telemetry/audit data. * Familiarity with the Model Context Protocol (MCP), tool registries, and agent orchestration patterns. * Postgres extension development in C or Rust, or contributions to the Postgres ecosystem. EDB is committed to supporting our employees’ overall well being by offering a range of benefits and resources to promote a healthy work-life balance and wellness. We provide access to CuraLinc to aid employees in health and wellness tips and practices, as well as Wellness Fridays extending to December 2026! Check out our career site for more information on perks and benefits and reach out to our Talent Acquisition team for region specific benefits. We know it takes a unique mix of people and skills to help us in our mission to supercharge Postgres, and we understand that not everyone will check every box. We’d love to hear from you and we want you to apply! EDB is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. EDB was built on a commitment to trust and respect each other and to embrace an array of people and ideas. These values remain at the center of our culture and are key to our company’s integrity. EDB does not seek or accept unsolicited resumes or CVs from recruitment agencies. EDB and its affiliates are not responsible for, and will not pay, any fees, commissions, or any other similar payment related to unsolicited resumes or CVs except as required in a written signed agreement between EDB and the recruitment agency or party requesting payment of a fee. #LI-Remote Show more [Apply now >](https://jobicy.com/jobs/155746-machine-learning-engineer-governance-ml-platform.md) > Annual salary information is not provided for this position. 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