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Remote mid-level generalist ML/AI role, metro locations, broad GenAI skillset increases applicant competition.
Advanced GenAI and healthcare compliance expectations moderately limit transferability across industries.
Extensive mandatory LLM, MLOps, cloud, and GenAI tool expertise increases shortlisting strictness.
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Design, develop, and deploy advanced AI and Generative AI solutions for healthcare technology platforms without access to PHI/PII or secured client data.
Build and optimize AI/Gen AI models (including multi-modal LLMs) using RAG architecture, Agentic AI frameworks, vector and graph databases, with end-to-end deployment in cloud/on-prem environments.
Integrate AI models via API development, implement ML Ops/LLM Ops for continuous monitoring and optimization, ensuring compliance with healthcare regulations and data privacy standards.
Bachelor’s or higher degree in Computer Science, AI, Data Science, Engineering, or related field.
2 to 15 years of experience in AI/ML engineering focused on development and deployment of AI solutions.
Proficiency in Python, TensorFlow, PyTorch; experience with fine-tuning LLMs (GPT, Gemini, Claude or similar), prompt engineering, and AI framework usage.
Experience with cloud platforms (AWS, Azure, GCP), MLOps, big data technologies (Spark, Hadoop, SQL, NoSQL).
Experienced in advancing healthcare AI applications with emphasis on regulatory compliance including HIPAA and CMS is preferred.
Able to architect and implement complex AI/Gen AI solutions using multi-modal models, RAG architecture, and AI operational pipelines.
Capable of collaborating across multiple stakeholders to translate business challenges into scalable, optimized AI-driven technology implementations.