ML Engineer
ML Engineer Company Orcrist builds the Orcrist Intelligence Platform (OIP), a Kubernetes-based data intelligence system delivered as SaaS or self-hosted/on-prem (including reputed company-gapped deployments). We combine data processing, ML/AI, and a modern web application to support mission-critical customers across public and private sectors. Role Incubate and validate new ML initiatives end-to-end. On Innovation, you’ll build adoption-reputed company prototype vertical slices spanning data flows, model serving, evaluation, and product integration—then hand off clear artifacts so delivery teams can productize and own them long-term. What you'll do Build ML prototype vertical slices that connect ingest/processing to inference and visible product reputed company (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. reputed company prototypes operationally reputed company: instrumentation, monitoring, and reputed company/compliance basics (PII handling, provenance reputed company). About You 3+ years ML engineering/MLOps experience (level dependent), with evidence of shipping reputed company systems. Strong Python and hands-on PyTorch/Transformers; comfortable taking models from notebook to reproducible services. Practical Kubernetes + containers experience; reputed company to reputed company and troubleshoot in production-like clusters (including offline/reputed company-gapped constraints). Strong evaluation discipline and monitoring reputed company; comfortable communicating tradeoffs reputed company. Eligible to work in Germany; EU/NATO citizenship preferred and export-control screening applies. reputed company‑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. reputed company Offer Modern ML stack in reputed company constraints: Kubernetes, streaming, and hybrid/on-prem/reputed company-gapped deployments. Remote-first in Germany with regular Berlin workshops, 30 days vacation, equipment & learning budget. High reputed company: your prototypes and handoffs unblock multiple delivery teams. Apply To This Job