Orcrist Technologies

Orcrist Technologies

Orcrist Technologies specializes in providing advanced technology solutions, including data analytics, AI applications, and cybersecurity, aimed at empowering businesses to innovate and transform through the use of artificial intelligence and data-driv...

Internet Software & Services

Description

  • Build ML prototype vertical slices that connect data ingestion and processing to inference and visible product outcomes such as search, insights, and UX flows.
  • Create evaluation harnesses and decision artifacts, including datasets, baselines, quality/latency/cost metrics, and go/no-go recommendations.
  • Package prototypes for adoption by containerizing services, defining reproducible deployments, and producing runbooks and checklists.
  • Partner with Research and Data Engineering on dataset curation, annotation loops, experiment tracking, and safe iteration.
  • Make prototypes operationally credible through instrumentation, monitoring, and basic security and compliance practices such as PII handling and provenance awareness.
  • Hand off clear artifacts so delivery teams can productize and own successful prototypes long term.

Requirements

  • 3+ years of ML engineering or MLOps experience, with evidence of shipping real systems.
  • Strong Python experience and hands-on work with PyTorch and Transformers.
  • Experience taking models from notebook workflows to reproducible services.
  • Practical Kubernetes and container experience, including deployment and troubleshooting in production-like clusters.
  • Ability to work in offline or air-gapped deployment environments.
  • Strong evaluation discipline and monitoring mindset, with the ability to communicate tradeoffs clearly.
  • Eligible to work in Germany; EU or NATO citizenship is preferred and export-control screening applies.
  • GPU serving and optimization experience with tools such as Triton, KServe, ONNX, or TensorRT is preferred.
  • Experience with streaming or pipeline tools such as Kafka, Ray, Beam, Flink, or Spark is preferred.
  • Experience with search, vector, or graph integrations is preferred.
  • German language skills at B1+ level are preferred.
  • Experience with regulated or public-sector datasets and workflows is preferred.

Benefits

  • Remote-first work in Germany with regular Berlin workshops.
  • 30 days of vacation.
  • Equipment budget.
  • Learning budget.
  • Opportunity to work on a modern ML stack in real-world constraints, including Kubernetes, streaming, and hybrid/on-prem/air-gapped deployments.
  • High-leverage role where your prototypes and handoffs can unblock multiple delivery teams.

Interested in this position?

Apply directly on the company website

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