Machine Learning Engineer

Orcrist TechnologiesRemote

Remote Full-time

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Experience Level

Mid to Senior

Qualifications

Qualifications 4 to 8+ years of experience in ML engineering or MLOps, with a proven track record of deploying models to production. Proficiency in Python and frameworks such as PyTorch/Transformers, along with experience using Triton/KServe or similar technologies. Familiarity with Kubernetes, GitOps, CI/CD practices, and GPU workload management. Strong understanding of evaluation metrics, monitoring techniques, and annotation workflows. Eligibility to work in Germany; export-control screening may be required for certain projects.

About the job

At Orcrist Technologies, we are pioneering the future of data intelligence with our Orcrist Intelligence Platform (OIP). This secure, Kubernetes-native system is designed for deployment as Software as a Service (SaaS) or can be self-hosted/on-premises, accommodating even air-gapped missions. Our mission is to seamlessly integrate data processing, machine learning, and user-centric design for defense, law enforcement, and corporate teams.

Role Overview

As a Machine Learning Engineer, you will be instrumental in productionizing NLP, audio, and document models that enhance the insight experiences provided by OIP. You will take full ownership of model packaging, deployment, monitoring, and evaluation, collaborating closely with research and product teams to ensure the delivery of reliable insights globally.

Your Responsibilities

Package and deploy various models (ASR, translation, OCR, NER, summarization) utilizing Triton/KServe on Kubernetes.
Develop evaluation pipelines (WER, BLEU, F1, latency, cost) and automate release gating processes.
Manage streaming and batch inference through Kafka, Temporal, and backfill tooling.
Monitor model performance and quality using Prometheus, Grafana, and Evidently; optimize inference costs and performance metrics.
Collaborate with TypeScript teams to design payload schemas, contracts, and establish human-in-the-loop feedback mechanisms.

Qualifications

4 to 8+ years of experience in ML engineering or MLOps, with a proven track record of deploying models to production.
Proficiency in Python and frameworks such as PyTorch/Transformers, along with experience using Triton/KServe or similar technologies.
Familiarity with Kubernetes, GitOps, CI/CD practices, and GPU workload management.
Strong understanding of evaluation metrics, monitoring techniques, and annotation workflows.
Eligibility to work in Germany; export-control screening may be required for certain projects.

Preferred Qualifications

Experience with Temporal, Beam/Flink, or Ray Serve; familiarity with ONNX/TensorRT optimization.
Proficiency in the German language (B1+) and experience with defense or public safety datasets.
Knowledge of WhisperX, DeepStream/GStreamer, or vector search integrations.

What We Offer

A modern MLOps stack including Triton, Temporal, Kafka, MLflow, Weights & Biases, Evidently, and Kubernetes.
A remote-first work environment in Germany, with regular meetups in Berlin, 30 days of vacation, and a budget for equipment and learning.

About Orcrist Technologies

Orcrist Technologies is at the forefront of data intelligence, offering a secure, Kubernetes-native platform designed to meet the needs of defense, law enforcement, and enterprise operations. Our innovative solutions combine advanced data processing with machine learning and user-friendly design to deliver insights that matter.

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Machine Learning Engineer

Orcrist Technologies

Full-time|Remote|Remote

Company Overview At Orcrist Technologies, we are pioneering the future of data intelligence with our Orcrist Intelligence Platform (OIP). This secure, Kubernetes-native system is designed for deployment as Software as a Service (SaaS) or can be self-hosted/on-premises, accommodating even air-gapped missions. Our mission is to seamlessly integrate data processing, machine learning, and user-centric design for defense, law enforcement, and corporate teams. Role Overview As a Machine Learning Engineer, you will be instrumental in productionizing NLP, audio, and document models that enhance the insight experiences provided by OIP. You will take full ownership of model packaging, deployment, monitoring, and evaluation, collaborating closely with research and product teams to ensure the delivery of reliable insights globally. Your Responsibilities Package and deploy various models (ASR, translation, OCR, NER, summarization) utilizing Triton/KServe on Kubernetes. Develop evaluation pipelines (WER, BLEU, F1, latency, cost) and automate release gating processes. Manage streaming and batch inference through Kafka, Temporal, and backfill tooling. Monitor model performance and quality using Prometheus, Grafana, and Evidently; optimize inference costs and performance metrics. Collaborate with TypeScript teams to design payload schemas, contracts, and establish human-in-the-loop feedback mechanisms. Qualifications 4 to 8+ years of experience in ML engineering or MLOps, with a proven track record of deploying models to production. Proficiency in Python and frameworks such as PyTorch/Transformers, along with experience using Triton/KServe or similar technologies. Familiarity with Kubernetes, GitOps, CI/CD practices, and GPU workload management. Strong understanding of evaluation metrics, monitoring techniques, and annotation workflows. Eligibility to work in Germany; export-control screening may be required for certain projects. Preferred Qualifications Experience with Temporal, Beam/Flink, or Ray Serve; familiarity with ONNX/TensorRT optimization. Proficiency in the German language (B1+) and experience with defense or public safety datasets. Knowledge of WhisperX, DeepStream/GStreamer, or vector search integrations. What We Offer A modern MLOps stack including Triton, Temporal, Kafka, MLflow, Weights & Biases, Evidently, and Kubernetes. A remote-first work environment in Germany, with regular meetups in Berlin, 30 days of vacation, and a budget for equipment and learning.

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Machine Learning Engineer

Orcrist Technologies

Full-time|Remote|Remote / Berlin

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Jan 28, 2026

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Machine Learning Engineer, Forward Deployed

Prior Labs

Full-time|On-site|Berlin

Join Our Innovative TeamAt Prior Labs, we are pioneering the development of foundation models that adeptly comprehend tabular data, which serves as the cornerstone of both scientific and business endeavors. While foundation models have revolutionized the fields of text and image processing, structured data has largely been overlooked. We are seizing the opportunity to address this $600 billion market and fundamentally transform how organizations manage scientific, medical, financial, and business data.Our Achievements: We stand at the forefront of structured data machine learning. Our TabPFN v2 model, featured in Nature, has set a new benchmark in tabular machine learning. Since its launch, we have enhanced our model capabilities over 20 times, achieved over 2.5 million downloads, garnered more than 5,500 stars on GitHub, and are witnessing rapid adoption across both research and industry sectors. We are currently developing the next generation of tabular foundation models and actively commercializing them in collaboration with global enterprises in Europe and the U.S.About Our Team: We are a compact, highly selective team of over 20 engineers and researchers, chosen from more than 5,000 applicants. Our team includes talents from industry giants like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. We are led by the creators of TabPFN and supported by renowned AI researchers, including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet our exceptional team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are experiencing rapid growth. This is an exciting opportunity to join us and contribute to shaping the future of structured data AI. Read our manifesto.Your ImpactIn this role, you will do more than simply deploy models; you will play a crucial role in delivering transformative solutions that redefine how organizations leverage data. You will work at the intersection of advanced AI technology and practical applications, collaborating closely with our key strategic partners.

Jan 31, 2026

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Machine Learning Engineer for Cloud Platform

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Full-time|On-site|Berlin

Join Our Innovative TeamAt Prior Labs, we are revolutionizing the way organizations interact with structured data, the cornerstone of science and business. While foundation models have significantly advanced the fields of text and image processing, structured data has largely been overlooked. We are seizing a $600 billion opportunity to transform how scientific, medical, financial, and business data are utilized.Leading the Charge: We are recognized as the premier organization in structured data machine learning. Our TabPFN v2 model, highlighted in Nature, has set a new benchmark in tabular machine learning. Our capabilities have expanded over 20 times since launch, with over 2.5 million downloads and 5,500+ stars on GitHub, leading to rapid adoption in both research and industry. We are now advancing the next generation of tabular foundation models and partnering with major enterprises across Europe and the US.Our Team: We are a tight-knit team of over 20 engineers and researchers, handpicked from a pool of more than 5,000 applicants, with backgrounds from renowned companies like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. Our team is guided by the creators of TabPFN and supported by leading AI experts such as Bernhard Schölkopf and Turing Award winner Yann LeCun. Get to know our team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are rapidly expanding. This is the perfect moment to join us and help shape the future of structured data AI. Explore our manifesto.

Sep 26, 2025

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