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) .