AI Solution Architect Healthcare
6 days ago
Title:
Medical Devices AI Solution Architect
Experience Required:
15+ Years
Location:
Greater Noida, 5 days work from office
Role Summary:
We are seeking a highly experienced Medical devices
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 medical devices
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 Medical devices 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, Neo4
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