Senior Data & ML Infrastructure Engineer (Xora Portfolio Company)
Core
Build and operate data and machine-learning infrastructure pipelines that transform large-scale scientific output into training-ready data and deploy models into production.
Role type
Senior IC data & ML infrastructure engineer
Builds
Data pipelines, model serving systems, and observability tools for scientific AI platforms
Domain
Applied AI, materials science, high-performance computing
Deliverable
production ML models | infrastructure
Required skills
Python, large-scale data systems (object storage, columnar formats, distributed compute), ML data pipelines (ingestion, curation, validation), Production MLOps (packaging, versioning, serving, monitoring), containers and orchestration (Docker, Kubernetes), workflow orchestrators (Airflow, Dagster, Flyte, Temporal), telemetry and observability (Prometheus, Grafana, OpenTelemetry)
Preferred skills
Data-quality tooling (Great Expectations, Evidently), experiment tracking (MLflow, Weights & Biases), model-serving stacks (Ray Serve, KServe, Kubeflow), scientific ML applications, atomistic-ML data tooling
Technologies
Python, Docker, Kubernetes, Airflow, Dagster, Flyte, Temporal, Prometheus, Grafana, OpenTelemetry, object storage, columnar formats, MLflow, Weights & Biases, Ray Serve, KServe, Kubeflow
Responsibilities
Build data pipelines for ingesting and curating large-scale scientific output; Implement validation and quality gates for data; Package, version, and deploy models with CI/CD; Run models through serving workflows for batch and online inference; Monitor deployed models for drift, latency, and anomalies; Design APIs and internal tools for engineers and scientists
Seniority
Senior, hands-on IC