Senior Data & ML Infrastructure Engineer — Hybrid Role

Xora Innovation; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

Elemynt, an early-stage startup by Xora Innovation, seeks an experienced engineer to own data and ML infrastructure, building pipelines for large-scale scientific output and the systems to train, deploy, and monitor models in customer environments. You will work end-to-end from data ingestion to model delivery.

Responsibilities include creating training-ready data formats, enabling fast queries, and implementing robust validation, observability, and CI/CD practices across development, staging,

Qualifications

• Bachelor's or Master's degree in Computer Science or a related engineering field
• 6+ years building and shipping production software with depth in data systems and ML infrastructure
• Strong Python and track record of shipping reliable systems end to end
• Hands-on experience with large-scale data systems: object storage, columnar formats, distributed query/compute engines
• Experience building data and ML data pipelines: ingestion, transformation, curation, validation and quality gates
• Production MLOps: packaging, versioning, serving, monitoring, and CI/CD for ML
• Hands-on with containers and orchestration (Docker, Kubernetes) and workflow orchestrators (Airflow, Dagster, Flyte, Temporal)
• Telemetry/monitoring: Prometheus, Grafana, OpenTelemetry to debug incidents
• Comfort across cloud and HPC, distributed multi-GPU, early-stage environments
• Any experience with ML tooling and data governance is a plus

Responsibilities

• Build the data pipelines that ingest, transform, and curate large-scale scientific output into efficient, training-ready formats on object storage
• Make data fast to query and cheap to reuse for analysis and downstream jobs
• Build ML data pipelines for training, fine-tuning, and reinforcement learning: curation, deduplication, formatting, evaluation sets
• Catch bad data early with validation and quality gates for schema, distribution, and completeness
• Package, version, and deploy models across development, staging, production with registries and reproducible builds
• Run models through CI/CD and serving workflows for batch, online, and asynchronous inference with safe rollout and quick diagnosis
• Monitor deployed models for drift, latency, and anomalies with automated checks
• Stand up dashboards, metrics, logs, and alerts surface data/model problems early
• Design APIs, services, and internal tools to make workflows reliable for engineers and scientists

Skills

Python

Production systems

ML infra

Data pipelines

Education

Bachelor's or Master's in Computer Science or related engineering field

Tools

Docker

Kubernetes

Airflow

Dagster

Flyte

Temporal

Prometheus

Grafana

OpenTelemetry

MLflow

Weights & Biases

Ray Serve

KServe

Kubeflow

Job description

Elemynt, an early-stage startup by Xora Innovation, seeks an experienced engineer to own data and ML infrastructure, building pipelines for large-scale scientific output and the systems to train, deploy, and monitor models in customer environments. You will work end-to-end from data ingestion to model delivery.

Responsibilities include creating training-ready data formats, enabling fast queries, and implementing robust validation, observability, and CI/CD practices across development, staging,