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.

Role Description

We’re looking for an AI Research Engineer to help us develop state-of-the-art AI products. You’ll work across the stack — from model research and algorithm design to efficient, scalable deployment and maintenance.

Typical projects may include:

• Improving and optimizing training algorithms
• Expanding and refining our RAG pipeline
• Fine-tuning and evaluating LLMs
• Scaling models for multi-GPU and cloud inference
• Building novel AI features for our portfolio
• Monitoring existing applications

This is an exciting opportunity to contribute to applied AI research that directly impacts our products and customers.

Qualifications

What You Need

• Master’s degree in computer science, AI or related field
• Software engineering skills and proficiency in Python (2+ year in a professional environment)
• Ability to read, understand, and implement ideas from scientific papers
• Strong experience in NLP and LLMs
• Excellent communication skills in English (both written and spoken)
• Open and curious mindset with a passion for continuous improvement

Nice To Have

• 5+ years of experience in software engineering
• PhD degree in a relevant field
• Comfortable with frameworks such as PyTorch, TensorFlow, Keras, or JAX
• Practical MLOps (cloud, containers, orchestration, monitoring) and data quality/labeling experience.
• experience with efficient inference deployments in the cloud
• Knowledge of traditional ML algorithms
• Exposure to Unix/Linux environments