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AI Architect, Life Sciences

AI Architect, Life Sciences

CoforgeNoida, Republic Of India, IN
12 days ago
Job description

Title : Life Sciences AI Solution Architect

Experience Required : 15+ Years

Location : Greater Noida, 5 days work from office

Role 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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