Orcrist Technologies
ML Engineer
Remote ML Engineering role with clear candidate location fit.
PostedJul 10, 2026
Eligible countries40 accepted countries
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Role overview
ML Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
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.
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Hiring flow
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