
AI DevOps
2 days ago
AI DevOps / Infrastructure Engineer
Company:
Dizzaroo Pvt Ltd
Location:
Pune
About Us
Dizzaroo is an AI-driven life sciences company developing intelligent solutions for
clinical research, oncology, and digital pathology
. Our teams work at the intersection of advanced AI engineering and disease biology to transform how pharma companies discover and develop new therapies.
We are looking for an
AI DevOps / Infrastructure Engineer
to design, implement, and manage our cloud and on-prem infrastructure that powers model training, inference, and secure application deployments. This role will directly influence the scalability, performance, and security of our AI platforms.
Responsibilities
- Define and implement the
overall infrastructure strategy
for AI model training and inference — across on-premise and cloud environments. - Build reliable and automated systems for
continuous deployment and monitoring
of AI applications and services. - Ensure
secure, compliant, and cost-efficient
operation of all infrastructure components. - Establish and maintain
information-security controls
in alignment with company policies (e.g., access management, data handling, logging, encryption). - Collaborate with AI, data, and product teams to
translate research prototypes into production systems
. - Drive
infrastructure optimization and standardization
to support rapid experimentation and scaling. - Contribute to documentation, disaster-recovery planning, and operational readiness reviews.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, or related field (or equivalent practical experience).
- 3–7 years of experience
in DevOps, Cloud, or Infrastructure Engineering — ideally supporting AI or data-intensive workloads. - Solid understanding of
multi-cloud environments
and containerized deployments. - Demonstrated ability to
automate workflows
, manage compute resources, and deliver secure production systems. - Familiarity with
information-security frameworks
(ISO 27001, HIPAA, or similar) is preferred.
Nice to Have
- Experience designing infrastructure for
GPU-based training or inference
. - Exposure to
pharma, healthcare, or regulated-data environments
. - Interest in
scaling AI products
from research to enterprise adoption.
What We Offer
- Opportunity to
build the core infrastructure powering next-generation AI in life sciences
. - Collaborative environment bridging
AI research, clinical development, and engineering
. - Competitive compensation and growth opportunities.
- Work on global AI initiatives solving important life science problems.
-
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