Senior ML Data Infrastructure Engineer

Xora Innovation; Singapore; Híbrido; SGD 166.000 - 269.000; Jornada completa

Descripción de la vacante

Elemynt is hiring in Singapore or the United States. The role focuses on building and operating data and ML infrastructure that powers the platform. You will own data pipelines, model packaging, deployment, and observability, with deployments in customers’ secure environments, on clusters, in their clouds, or hybrid setups.

You will implement CI/CD, monitoring, and dashboards; design APIs and internal tools to keep workflows reliable and usable by engineers and scientists.

Formación

• Bachelor's or Master's in Computer Science or related engineering field; 6+ years building and shipping production software with data systems and ML infrastructure.
• Strong Python and ability to ship reliable end-to-end systems.
• Hands-on with large-scale data systems: object storage, columnar/array formats, distributed engines.
• Experience building data & ML data pipelines: ingestion, transformation, validation gates.
• Production MLOps: packaging, versioning, serving, monitoring via registries and CI/CD.
• Deep experience with containers/orchestration (Docker, Kubernetes) and workflows (Airflow/Dagster/Flyte/Temporal).
• Telemetry: instrument production systems; debug with logs/metrics (Prometheus, Grafana, OpenTelemetry).
• Cloud and HPC exposure, distributed multi-GPU, ownership of end-to-end fragile systems.

Responsabilidades

• Build data pipelines transforming large-scale scientific output into training-ready formats.
• Make data fast to query and cheap to reuse for analysis and downstream jobs.
• Create ML data pipelines for training, fine-tuning, and RL: curation, deduplication, formatting, eval sets.
• Implement data validation/quality gates before training or inference.
• Package, version, and deploy models with registries and reproducible builds.
• Run CI/CD and serving workflows for batch, online, and asynchronous inference.
• Monitor models for drift, latency, and anomalies with automated checks.
• Stand up dashboards, metrics, logs, and alerts for data/model issues.
• Design APIs and internal tools to make workflows reliable for engineers and scientists.

Conocimientos

Python

Data systems

ML infrastructure

MLOps

Containers & orchestration

Telemetry & monitoring

Cloud & HPC

Educación

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

Herramientas

Docker

Kubernetes

Airflow

Dagster

Flyte

Temporal

Prometheus

Grafana

OpenTelemetry

MLflow

Weights & Biases

Ray Serve

KServe

Kubeflow

Descripción del empleo

Elemynt is hiring in Singapore or the United States. The role focuses on building and operating data and ML infrastructure that powers the platform. You will own data pipelines, model packaging, deployment, and observability, with deployments in customers’ secure environments, on clusters, in their clouds, or hybrid setups.

You will implement CI/CD, monitoring, and dashboards; design APIs and internal tools to keep workflows reliable and usable by engineers and scientists.