Senior Data & ML Infrastructure Engineer

Xora Innovation

Senior Data & ML Infrastructure Engineer designing and managing data pipelines and ML models for AI applications. Collaborating with engineering teams to ensure data integrity and system reliability.

Posted 8/2/2026full-timeSingapore • 🇸🇬 SingaporeSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying ML data pipelines, ensuring data quality and model performance through robust monitoring and validation. Proficient in using containers and orchestration tools to manage production systems across cloud and HPC environments.

Highest-signal resume keywords

Python ProgrammingML Data Pipeline DevelopmentProduction MLOps ExperienceContainerization (Docker, Kubernetes)Data Systems Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationData CurationModel PackagingModel VersioningModel MonitoringCI/CD for MLSchema ValidationTelemetry InstrumentationDistributed Query Engines

Tools & Technologies

AirflowDagsterFlyteTemporalPrometheusGrafanaOpenTelemetryObject StorageColumnar Data FormatsMulti-GPU Systems

Industry Keywords

Machine Learning InfrastructureData Quality GatesModel RegistriesCloud ComputingHigh-Performance Computing

Tech Stack

Tools & technologies

AirflowCloudDockerGrafanaKubernetesPrometheusPython

About the role

Key responsibilities & impact

Build the data pipelines that ingest, transform, and curate large-scale scientific output into efficient, training-ready formats on object storage.
Make that data fast to query and cheap to reuse, so analysis and downstream jobs aren’t left waiting on it.
Build the ML data pipelines for training, fine-tuning, and reinforcement learning: curation, deduplication, formatting, and the evaluation sets that keep training honest.
Catch bad data early, with validation and quality gates that check schema, distribution, and completeness before it reaches a model.
Package, version, and deploy models across development, staging, and production, with registries and reproducible builds that keep every deployment traceable.
Run models through CI/CD and serving workflows for batch, online, and asynchronous inference, with safe rollout, rollback, and quick diagnosis when something breaks.
Monitor deployed models for drift, degradation, latency, and anomalies, with automated regression checks that flag trouble before users do.
Stand up dashboards, metrics, logs, and alerts that surface data and model problems while they’re still small.
Design the APIs, services, and internal tools that make these workflows reliable and easy for engineers and scientists to use.

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science or a related engineering field, and 6+ years building and shipping production software, with real depth across data systems and ML infrastructure.
Strong Python, and a track record of shipping reliable systems end to end that other people end up depending on.
Hands-on experience with large-scale data systems: object storage, efficient columnar and array data formats, and distributed query and compute engines.
Experience building data and ML data pipelines: ingestion, transformation, curation, and the validation and quality gates that catch problems before they reach training or inference.
Production MLOps experience: packaging, versioning, serving, and monitoring models for drift, latency, and anomalies, backed by model registries and CI/CD for ML.
Deep hands-on experience with containers and orchestration (Docker, Kubernetes) and workflow orchestrators such as Airflow, Dagster, Flyte, or Temporal.
Experience instrumenting production systems and using their telemetry, logs, and metrics (Prometheus, Grafana, OpenTelemetry, or similar) to debug real incidents.
Comfort working across cloud and HPC, including distributed multi-GPU, and owning ambiguous systems end to end in an early-stage setting with little scaffolding.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Xora Innovation Website LinkedIn All Job Openings 11 - 50 employees Founded 2019 💼 Consulting 🏥 Healthcare 📦 Logistics Consulting
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Logistics Xora Innovation is a venture capital firm that partners with exceptional entrepreneurs in the deep tech space, focusing on transforming essential industries. Xora provides financial support and commitment to innovative companies that are building tomorrow's global infrastructure across three key sectors: Compute & Communications, Climate & Energy, and AI in Physical Industries. Senior Data & ML Infrastructure Engineer Job not on LinkedIn 🔥 1 hour ago 🏢🏡 Singapore – Hybrid ⏰ Full Time 🟠 Senior 👷 Infrastructure Engineer Airflow Cloud Docker Grafana Kubernetes Prometheus Python Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Build the data pipelines that ingest, transform, and curate large-scale scientific output into efficient, training-ready formats on object storage.
Make that data fast to query and cheap to reuse, so analysis and downstream jobs aren’t left waiting on it.
Build the ML data pipelines for training, fine-tuning, and reinforcement learning: curation, deduplication, formatting, and the evaluation sets that keep training honest.
Catch bad data early, with validation and quality gates that check schema, distribution, and completeness before it reaches a model.
Package, version, and deploy models across development, staging, and production, with registries and reproducible builds that keep every deployment traceable.
Run models through CI/CD and serving workflows for batch, online, and asynchronous inference, with safe rollout, rollback, and quick diagnosis when something breaks.
Monitor deployed models for drift, degradation, latency, and anomalies, with automated regression checks that flag trouble before users do.
Stand up dashboards, metrics, logs, and alerts that surface data and model problems while they’re still small.
Design the APIs, services, and internal tools that make these workflows reliable and easy for engineers and scientists to use. 🎯 Requirements
Bachelor’s or Master’s degree in Computer Science or a related engineering field, and 6+ years building and shipping production software, with real depth across data systems and ML infrastructure.
Strong Python, and a track record of shipping reliable systems end to end that other people end up depending on.
Hands-on experience with large-scale data systems: object storage, efficient columnar and array data formats, and distributed query and compute engines.
Experience building data and ML data pipelines: ingestion, transformation, curation, and the validation and quality gates that catch problems before they reach training or inference.
Production MLOps experience: packaging, versioning, serving, and monitoring models for drift, latency, and anomalies, backed by model registries and CI/CD for ML.
Deep hands-on experience with containers and orchestration (Docker, Kubernetes) and workflow orchestrators such as Airflow, Dagster, Flyte, or Temporal.
Experience instrumenting production systems and using their telemetry, logs, and metrics (Prometheus, Grafana, OpenTelemetry, or similar) to debug real incidents.
Comfort working across cloud and HPC, including distributed multi-GPU, and owning ambiguous systems end to end in an early-stage setting with little scaffolding. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Senior Infrastructure Architect – Hybrid Datacenter, Public Cloud Foundations 🕒 February 12 OCBC 10,000+ employees 🛡️ Insurance 🏦 Banking 💸 Finance Website LinkedIn All Job Openings Lead architecture and hands-on technical oversight of hybrid infrastructure at OCBC bank. Oversee design, implementation, and operations involving datacenters and public cloud foundations. 🏢🏡 Singapore – Hybrid ⏰ Full Time 🟠 Senior 👷 Infrastructure Engineer Cloud Firewalls Flux VMware View More Infrastructure Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Is Remote Rocketship legit? Privacy policy Terms of service Job board SEO course Remote Job Search MasterClass AI Apply Copilot OpenClaw job finder Find jobs using your resume Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs