Summary
✨ AI‑Generated
A machine learning engineering role focused on building, deploying, and operating production ML systems for secure, document-heavy business workflows. You will help develop intelligent capabilities for searching, understanding, processing, and protecting sensitive information within large document collections.
Highlights
Opportunity to build, deploy, and operate machine learning systems for secure document-intensive workflows. The role combines AI innovation with production engineering and work on technologies that help users extract value from large document collections.
Description
Company Description
Imprima specializes in reducing the stress of managing large and complex deals with numerous moving parts.
Our core values of security, reliability, service, and innovation ensure our clients can focus on their deals with complete peace of mind, never worrying about data integrity.
As pioneers of highly secure Virtual Data Rooms (VDRs) and self-service document management applications, our breakthrough AI technology keeps us at the forefront of the industry.
Our advanced platform allows high-level stakeholders to access a wealth of reports, assign varied permissions and access rights, and provides admins with complete visibility into all document touch points — who viewed them, for how long, and any alterations made.
Our AI features, including document Q&A and automated PII redaction, help deal teams find what matters across thousands of documents.
Role Description
We're looking for a Machine Learning Engineer to build, deploy and operate the ML systems behind our products, with a strong focus on our Azure cloud environment.
You'll take models from prototype to production and keep them running reliably at scale.
Typical projects may include:
Writing clean, well-tested Python services and pipelines: APIs, batch jobs and data processingDeploying and operating ML services on Azure (AKS, Azure Container Apps, Azure Functions), using Managed Identity for secret-free access to resourcesManaging infrastructure as code with TerraformBuilding and maintaining CI/CD pipelines for model and infrastructure releasesContainerizing ML workloads with Docker and running them on Kubernetes, including GPU workloadsSetting up monitoring, alerting and tracing with Application Insights, and hardening existing production systemsOperating our vector database in production: sharding, replication, backup and restoreWorking with research to optimize models for production inference (quantization, ONNX, vLLM/SGLang)This is an opportunity to own our ML systems from development through production.
We're still shaping how AI engineering works at Imprima: the tooling, the standards, the way work moves from prototype to production.
You'll help lay that foundation rather than just work within it, together with a small AI R&D team that gives you plenty of autonomy.
Qualifications
What You Need
Bachelor's degree in computer science, engineering or a related field4+ years of professional Python development: clean, typed and tested code Strong hands-on experience with Azure or another major cloud platform: managed Kubernetes, container platforms, serverless functions, identity and access management, and monitoringDocker and Kubernetes in production, including GPU workloadsExperience building CI/CD pipelines Linux and bash scriptingSelf-sufficient and high-agency: you take ownership, make decisions and move things forward on your ownExcellent communication skills in English, both written and spokenNice To Have
PyTorch experienceUnderstanding of ML fundamentals: model evaluation, embeddings, LLM inferenceModel optimization and adaptation: ONNX, quantization, LoRAExperience with vector databasesServing LLMs with vLLM or SGLang.NET experience, ideally with Azure Functions (our frontend is .NET)Master's degree in computer science, AI or a related field