Experience Level: 10+ years.
Location: Bangalore.
About Datafoundry:
Datafoundry is an AI first company with solutions to accelerate digital transformation. As part of our initial focus
on the Life Sciences industry, we have built AI-automation products in the Safety Vigilance domain. Datafoundry
has multiple AI/ML algorithms that can solve digitalization problems across industry sectors such as Health Care,
Utilities, Aerospace and Defence, Manufacturing, Banking and Financial sectors.
Job Description:
We are looking for a visionary AI/ML Architect who combines deep technical expertise with
strong leadership capabilities to drive the development of cutting-edge AI solutions. In this
role, you will lead the architecture of intelligent systems across computer vision, NLP, and
reinforcement learning domains, with a focus on scalability, performance, availability and
real-world impact. You’ll play a pivotal role in shaping our AI strategy, mentoring technical
teams, and bringing innovative ideas to life especially in the context of healthcare and clinical
data environments. Prior exposure to the clinical or healthcare domain is highly desirable.
Roles and Responsibilities:
- 1. Conceptualize and architect AI solutions in the face of uncertain and evolving
requirements. - 2. Lead the design, development, and scaling of AI platforms and products.
- 3. Define and implement non-functional requirements (NFRs) such as scalability,
reliability, and performance. - 4. Document system and solution architectures using UML and industry-standard practices.
- 5. Drive innovation in AI/ML technologies to continuously enhance product capabilities.
- 6. Provide technical mentorship and foster growth within the engineering team.
Required skills:
- 1. Proven experience in developing computer vision models and solutions.
- 2. Deep expertise in Natural Language Processing (NLP), including:
- 3. Fine-tuning Named Entity Recognition (NER) models.
- 4. Customizing and fine-tuning LLMs (Large Language Models) and micro-LLMs
- 5. Conversational bots.
- 6. Knowledge of agentic-AI
- 7. Strong understanding of Explainable AI (XAI) methods and tools for ML
model interpretability. - 8. Experience developing Reinforcement Learning (RL)-based models.
- 9. Expertise in building data lakes and implementing data fabric architectures.
- 10. Knowledge of ontologies and semantic modeling for domain-specific
knowledge representation. - 11. End-to-end experience with data and ML pipeline engineering
- 12. Experience operating ML stack in a hybrid (including clouds and on-premises)
environment. - 13. Hands-on with MLOps tools such as MLflow, Kubeflow, or similar frameworks
for model lifecycle management.
Join our team at Datafoundry to be part of an exciting journey as we revolutionize the way
organizations leverage data to gain a competitive advantage. We offer attractive compensation and
bonus package, a flexible remote work environment, and ample opportunities for professional
growth.