Resumen del rol

ML Engineer

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

What you'll do

  • Build ML prototype vertical slices that connect ingest/processing to inference and visible product outcomes (search, insights, UX flows).
  • Create evaluation harnesses and decision artifacts: datasets, baselines, quality/latency/cost metrics, and go/no-go recommendations.
  • Package prototypes for adoption: containerize services, define reproducible deployments, and produce runbooks/checklists.
  • Partner with Research and Data Engineering on dataset curation, annotation loops, experiment tracking, and safe iteration.
  • Make prototypes operationally credible: instrumentation, monitoring, and security/compliance basics (PII handling, provenance mindset).

About You

  • 3+ years ML engineering/MLOps experience (level dependent), with evidence of shipping real systems.
  • Strong Python and hands-on PyTorch/Transformers; comfortable taking models from notebook to reproducible services.
  • Practical Kubernetes + containers experience; able to deploy and troubleshoot in production-like clusters (including offline/air-gapped constraints).
  • Strong evaluation discipline and monitoring mindset; comfortable communicating tradeoffs clearly.
  • Eligible to work in Germany; EU/NATO citizenship preferred and export-control screening applies.

Nice‑to‑haves

  • GPU serving/optimization experience (Triton/KServe, ONNX/TensorRT, batching, quantization).
  • Streaming/pipeline tooling (Kafka, Ray, Beam/Flink/Spark) and search/vector/graph integrations.
  • German language (B1+) and/or experience with regulated/public-sector datasets and workflows.

What We Offer

  • Modern ML stack in real constraints: Kubernetes, streaming, and hybrid/on-prem/air-gapped deployments.
  • Remote-first in Germany with regular Berlin workshops, 30 days vacation, equipment & learning budget.
  • High leverage: your prototypes and handoffs unblock multiple delivery teams.
Roles similares

Mantén una lista de respaldo.

Ver stack
FocoML EngineeringÁrea del rol
Señal de senioritySeniorNivel del candidato
StackKubernetes, Python, SparkSkills principales
Ubicación40 países aceptadosElegibilidad

Stack

Usa estas tags para comparar roles remotos similares.

Elegibilidad de ubicación

Candidatos deberían aplicar solo cuando el país del perfil aparece aquí.

Flujo de contratación

WithMira muestra el rol y luego envía candidatos a la aplicación de la empresa.

1Revisa fit del rol, stack y elegibilidad de ubicación en WithMira.
2Abre la página de aplicación de la empresa desde el link rastreado.
3Guarda el rol o suscríbete a oportunidades similares antes de salir.
Aplicar en el sitio de la empresaSitio de la empresaAbrir link