Life Sciences AI Solution Architect
4 weeks ago
Title: Life Sciences AI Solution ArchitectExperience Required: 15+ YearsLocation: Greater Noida, 5 days work from officeRole Summary:We are seeking a highly experienced Life Sciences AI Solution Architect with deep expertise in AI/ML solutioning and architecture within the pharmaceutical and biotech domains. The ideal candidate will have a strong understanding of pharma data, relevant regulatory frameworks, and hands-on experience in designing and deploying AI/ML solutions across the life sciences value chain—including R&D, manufacturing, supply chain, commercial operations, and patient safety. This role demands strategic thinking, technical leadership, and cross-functional collaboration to drive innovation and transformation.Key Responsibilities:- Design and architect end-to-end AI/ML solutions for pharma/biotech use cases. - Apply MLOps methodologies for efficient model development, deployment, and monitoring. - Leverage Cognitive AI techniques such as NLP, Computer Vision, Speech, and Conversational AI. - Develop and implement Document AI and Generative AI solutions, including custom LLMs. - Ensure seamless integration of AI solutions into cloud platforms (AWS, Azure, GCP). - Deliver and maintain production-grade ML systems with high scalability and reliability. - Provide technical leadership and mentorship to AI/ML teams. - Collaborate with data scientists, ML engineers, and business stakeholders to transition prototypes to production. - Prepare comprehensive documentation for architecture, design, and implementation. - Stay current with emerging trends in AI, LLMs, MLOps, and life sciences technologies.Mandatory Skills:- 8+ years in AI/ML, with 3+ years in life sciences AI (pharma/biotech). - Proven experience in AI, ML, MLOps, Text Analytics, Generative AI. - Strong programming skills in Python and Java. - Experience with ML frameworks: TensorFlow, PyTorch, Keras, Scikit-learn. - Hands-on with cloud platforms: AWS, Azure, GCP. - Proficient in ML architectures: Ensemble Models, SVM, CNN, RNN, Transformers. - NLP tools: NLTK, SpaCy, Gensim. - MLOps tools: Kubeflow, MLflow, Azure ML. - Experience in Responsible AI, LangChain, and Vector Databases. - Workflow tools: Airflow. - Microservices architecture and API development using FastAPI, Flask, Django. - Database expertise: SQL, NoSQL (MongoDB, Postgres, Neo4j).
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