ABOUT US

Smart Reporting is a modern healthcare IT company revolutionizing the way radiologists create and manage clinical reports. Our platform empowers radiology professionals with structured reporting tools that increase efficiency, improve diagnostic quality, and enable data-driven insights. With over 150 employees and a presence in leading healthcare systems, we’re growing fast, and so are our ambitions.
We are looking for a Senior AI Engineer (all genders) to help shape the next generation of our intelligent reporting solutions by integrating cutting-edge AI/NLP technologies directly into clinical workflows.

YOUR ROLE

As a Senior AI Engineer, you will be at the forefront of building AI-powered features that enable smarter and more intuitive radiology reporting. You will drive initiatives such as:

• Summarization: Design models that can synthesize free-text and structured content (e.g., findings, clinical context) into concise diagnostic impressions.
• Clinical Note Consistency Checks: Build models to identify and flag inconsistencies in reports (e.g., laterality errors, body part mismatches, gender inconsistencies).
• Conversational and Natural Speech Input: Develop solutions to allow radiologists to informally describe cases and convert them into clinical semi-structured reports.

You will collaborate closely with a team of product managers, UX designers, medical doctors, and AI/software engineers who deeply understand the clinical workflow: as the seniormost AI expert, your mentorship and ability to explain complex ideas simply are essential.

YOUR RESPONSIBILITIES

• Drive the design and implementation of AI/NLP features for clinical reporting in close collaboration with product and engineering teams.
• Build and integrate LLM-based systems into our product suite.
• Fine-tune and evaluate models using approaches such as LoRA, instruction tuning, and parameter-efficient tuning.
• Apply classical NLP techniques (e.g., BERT, NER, text classification) where appropriate.
• Translate research and theory into practical applications in production.
• Collaborate cross-functionally with engineers, clinicians, and product teams.
• Mentor and support software developers to grow AI/ML skills across the company.