Experience:

• 2+ years of hands-on experience in end-to-end AI/ML development lifecycle
• Software development experience at a healthcare company, particularly in the provider space
• Experience with EHRs or related healthcare data domains
• Proven experience developing AI algorithms using real-world healthcare datasets and production pipelines

Qualification:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field

Responsibilities:

• Fine-tune and evaluate LLMs for healthcare use cases
• Build multimodal AI systems integrating text, structured medical data, and images
• Optimize models for accuracy, latency, and resource efficiency
• Evaluate and integrate STT and TTS models into conversational interfaces
• Customize foundation models using domain adaptation and prompt engineering
• Develop and productionalize AI algorithms using healthcare-specific data
• Write clean, reusable code for model training, evaluation, deployment, and integration
• Maintain reproducibility, version control, and experiment tracking
• Implement continuous learning workflows with real-time feedback
• Build and support voice assistant applications for clinical or patient use
• Process and curate large-scale structured and unstructured healthcare datasets
• Implement data privacy controls compliant with HIPAA, GDPR, and internal policies
• Design synthetic data generation strategies to augment training
• Handle noisy, imbalanced, or incomplete data through preprocessing and enrichment
• Perform and validate evaluation benchmarks and gold standard datasets
• Assess and address model bias, drift, explainability, and reliability
• Perform unit and integration testing for AI pipelines
• Apply responsible AI best practices and contribute to fairness, ethics, and safety guidance
• Participate in Agile workflows including stand-ups, sprint reviews, and retrospectives
• Document design, testing protocols, and implementation details
• Stay current on advances in GenAI, foundation models, STT/TTS, and multimodal learning
• Evaluate emerging tools and frameworks for platform integration
• Lead or contribute to knowledge-sharing discussions, demos, and architectural reviews
• Identify opportunities to improve scalability, safety, and impact of AI systems

Additional responsibilities:

• Collaborate across engineering, data, clinical, and product teams
• Tailor technical concepts to non-technical stakeholders
• Work in a fast-paced, agile environment with cross-functional collaboration
• Maintain strong documentation habits and collaborative coding practices
• Understand privacy, ethics, and risk mitigation around AI and healthcare data

Nice to have:

• Experience building voice assistants or conversational AI interfaces

More skills:

PyTorch, TensorFlow, Training and fine-tuning large language models (LLMs), NLP/NLU techniques, Speech-to-text (STT) models (e.g., Whisper, Elevenlabs), Text-to-speech (TTS) models (e.g., Elevenlabs), Retrieval-augmented generation (RAG), API deployment, Azure, Evaluation techniques (BLEU, ROUGE, accuracy, recall, human-in-the-loop validation)

Other:

• Mission-driven environment focused on improving healthcare precision care and patient engagement
• Company recognized by KLAS Research, Fierce Healthcare, and AVIA Marketplace in 2024
• Part of SymphonyAI Group with extensive R&D investment and large healthcare data assets
• Equal opportunity employer committed to diversity and inclusion