Senior ML Infrastructure Engineer - Data Pipelines & MLOps

Xora Innovation; San Diego (CA); Hybrid; USD 180,000 - 250,000; Full time

Job summary

Elemynt, part of Xora Innovation, is building data and ML infrastructure that turns research into production-ready models. This role focuses on pipelines, data formats, and reliable packaging, serving, and monitoring in customer environments across clouds and on-premise clusters.

You will own end-to-end data and ML pipelines, ensure observability, and ship model tooling with CI/CD and robust dashboards for engineers and scientists.

Qualifications

• Bachelor’s or Master’s degree in CS or related field with 6+ years of production software experience.
• Strong Python with a track record of shipping end-to-end, reliable systems.
• Experience with large-scale data systems: object storage, columnar formats, and distributed query/compute engines.
• Experience building data and ML data pipelines: ingestion, transformation, curation, and validation gating.
• Production MLOps: packaging, versioning, serving, monitoring, and CI/CD for ML.
• Hands-on containers/orchestration (Docker, Kubernetes) and workflow tools (Airflow, Dagster, Flyte, Temporal).
• Telemetry/logging/metrics instrumentation to debug incidents.
• Comfort across cloud and HPC, distributed multi-GPU, in early-stage settings.

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 the ML data pipelines for training, fine-tuning, and reinforcement learning: curation, deduplication, formatting, and eval sets.
• Catch bad data early with validation and quality gates that check schema, distribution, and completeness.
• Package, version, and deploy models across development, staging, and production with registries and reproducible builds.
• Run 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 regression checks.
• Stand up dashboards, metrics, logs, and alerts surface data and model problems early.
• Design the APIs, services, and internal tools that make these workflows reliable and easy for engineers and scientists to use.

Skills

Python

Production software

Distributed data systems

ML infrastructure

Docker

Kubernetes

Airflow

Dagster

Flyte

Temporal

Prometheus

Grafana

OpenTelemetry

Cloud & HPC

CI/CD for ML

Education

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

Tools

Docker

Kubernetes

Airflow

Dagster

Flyte

Temporal

MLflow

Weights & Biases

Ray Serve

KServe

Kubeflow

Prometheus

Grafana

Job description

Elemynt, part of Xora Innovation, is building data and ML infrastructure that turns research into production-ready models. This role focuses on pipelines, data formats, and reliable packaging, serving, and monitoring in customer environments across clouds and on-premise clusters.

You will own end-to-end data and ML pipelines, ensure observability, and ship model tooling with CI/CD and robust dashboards for engineers and scientists.