Life Sciences AI Solution Architect

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

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)