FluteSpace is an early-stage HealthTech company building next-generation AI copilots for medical imaging and clinical documentation. Our platform leverages ambient speech dictation, proprietary generative AI models, and structured clinical knowledge graphs to automate radiology reporting, eliminate administrative burden, and reduce clinician burnout. By converting unstructured ambient audio and real-time clinical notes into structured, accurate reports, FluteSpace empowers healthcare professionals to spend less time typing and more time caring for patients.

​We are seeking an ambitious, mission-driven Software / Machine Learning Engineering Intern to join our founding engineering team for the summer. In this role, you will work hands-on with cutting-edge LLM orchestration, speech-to-text pipelines, and high-performance workflow integrations designed for clinical workstations.

This internship offers high ownership, direct collaboration with founding engineers and practicing clinicians, and the opportunity to deploy AI directly into real-world healthcare environments.

• Core Product Development: Build and maintain scalable backend microservices, real-time web applications, and browser extensions designed for seamless integration into radiology workstations.

• Speech & NLP Engineering: Assist in tuning ambient speech recognition models, prompt orchestration pipelines, and domain-adapted LLMs to extract structured clinical findings, impressions, and ICD/CPT codes.

• Clinical Knowledge Bases: Help construct and maintain medical terminology databases and custom language models to ensure clinical accuracy and eliminate hallucinations.

• Evaluation & Benchmarking: Design automated test suites and evaluation harnesses to measure transcription latency, entity extraction accuracy, and report safety.

• Rapid Prototyping: Collaborate closely with product leads and clinicians to rapidly prototype, test, and iterate on high-impact features based on user feedback.

• ​Academic Background: Currently pursuing a Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Biomedical Informatics, Electrical Engineering, or a related technical field.

• Programming Skills: Strong proficiency in Python and/or modern JavaScript/TypeScript (React, Node.js).

• AI/ML Concepts: Hands-on experience or coursework in Natural Language Processing (NLP), Large Language Models (LLMs), prompt engineering, or machine learning frameworks (e.g., PyTorch, Hugging Face, LangChain, LlamaIndex).

• System Design & Tools: Familiarity with RESTful APIs, WebSockets, Git version control, and cloud environments (AWS, GCP, or Azure).

• Mindset: High curiosity, strong problem-solving skills, and comfort operating in a fast-paced, iterative startup setting.

• Experience building Chrome extensions or desktop integrations.

• Familiarity with healthcare standards and terminologies (DICOM, HL7, FHIR, SNOMED CT, RadLex).

• Prior internship or project experience working on production-level generative AI applications.

• Competitive internship stipend.

• Mentorship from experienced engineers and founders in AI and healthcare.

• Direct exposure to startup operations and clinical product strategy.