AI DevOps

3 weeks ago

Pune Maharashtra India, Maharashtra Dizzaroo Pvt Ltd Full time
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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