ML Engineer
Orcrist Technologiesabout 2 months ago
Remote, WorldwideMid Level / Senior
Responsibilities
- Package and deploy models (ASR, translation, OCR, NER, summarization) using Triton/KServe on Kubernetes.
- Build evaluation pipelines (WER, BLEU, F1, latency, cost) and automate release gating.
- Operate streaming and batch inference via Kafka, Temporal, and backfill tooling.
- Monitor drift and quality with Prometheus, Grafana, and Evidently; optimize inference cost and performance.
- Collaborate with TypeScript teams on payload schemas, contracts, and human-in-the-loop feedback loops.
Requirements
- 4–8+ years of ML engineering/MLOps experience, shipping models to production.
- Strong proficiency in Python and PyTorch/Transformers, with experience in Triton/KServe or similar.
- Comfortable with Kubernetes, GitOps, CI/CD, and GPU workload operations.
- Knowledge of evaluation metrics, monitoring, and annotation workflows.
- Eligible to work in Germany; export-control screening required for certain programs.
Benefits
- Access to a modern MLOps stack including Triton, Temporal, Kafka, and Kubernetes.
- Remote-first work environment in Germany with regular Berlin meetups.
- 30 days of vacation and a budget for equipment and learning.
Tech Stack
Categories
AI & MLData Engineering