Artificial Intelligence Engineer

Experience : 3 - 12 Years

Location : Remote

Industry : Healthcare / Precision Medicine / Life Sciences

Role Objective :

We are seeking a visionary AI Engineer/Scientist to architect and deploy intelligent systems that transform complex, unstructured clinical data into actionable medical insights. You will own the lifecycle of AI solutionsfrom the first spark of ideation to the deployment of scalable, production-grade models that impact patient outcomes and drug discovery.

Key Responsibilities :

End-to-End AI Development (Ideation to Execution) :

• Strategic Ideation : Collaborate with clinical experts to identify high-impact AI opportunities in oncology, genomics, and patient care.
• R&D & Prototyping : Design and build Proof-of-Concepts (POCs) using the latest in Generative AI, NLP, and Deep Learning.
• Production Engineering : Transition models from local notebooks to scalable cloud microservices (AWS/Azure/GCP) using Docker and Kubernetes.

Advanced Technical Implementation :

• Agentic Workflows : Build multi-agent systems (using LangGraph, CrewAI, or AutoGen) to automate complex data extraction and reasoning tasks.
• Retrieval-Augmented Generation (RAG) : Architect advanced RAG pipelines with semantic reranking and hybrid search to query massive clinical repositories.
• Model Optimization : Fine-tune LLMs/SLMs using techniques like LoRA, QLoRA, and Distillation to ensure high performance at optimized costs.

Team & Stakeholder Leadership :

• Technical Mentorship : Lead code reviews and set the standard for high-quality, reproducible AI research and engineering.
• Cross-Functional Collaboration : Serve as the technical bridge between data engineering, product teams, and clinical stakeholders.

Required Technical Skills :

• Programming : Mastery of Python (Advanced OOP, MLOps patterns) and SQL.
• Frameworks : LangChain, PyTorch, TensorFlow, FastAPI, and Hugging Face.
• Generative AI : Expert knowledge of Transformers, Prompt Engineering, and Vector Databases (Pinecone, Milvus, ChromaDB).
• Data Engineering : Experience with Spark, Databricks, and handling PHI (Protected Health Information) data.
• Computer Vision (Optional) : Familiarity with OCR/Vision-Language Models (VLMs) for medical report parsing.

Qualifications :

• Bachelors, Masters, or PhD in Computer Science, Data Science, Bioinformatics, or a related quantitative field.
• 3- 12 years of professional experience in an AI-centric role.
• Proven track record of deploying at least 2-3 enterprise-scale AI systems serving real-world traffic.