37:I[536569,["/_next/static/chunks/00ybbpx68_xw2.js","/_next/static/chunks/02jb5pnj98qe_.js","/_next/static/chunks/0i.l9589uvx0j.js","/_next/static/chunks/09xwjailhp6jd.js","/_next/static/chunks/0h7y588v_o8wu.js","/_next/static/chunks/03e85xkns9n81.js"],"default"] 28:["$","span","Python",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Python"}] 29:["$","span","TensorFlow",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"TensorFlow"}] 2a:["$","span","PyTorch",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"PyTorch"}] 2b:["$","span","CI/CD",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"CI/CD"}] 2c:["$","span","Kubernetes",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Kubernetes"}] 2d:["$","span","Docker",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Docker"}] 2e:["$","span","SQL",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"SQL"}] 2f:["$","span","System Design",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"System Design"}] 30:["$","span","Science",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Science"}] 31:["$","span","Data Science",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Data Science"}] 32:["$","span","Big Data",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Big Data"}] 33:["$","span","Data",{"className":"text-xs font-medium bg-[var(--color-brand-50)] text-[var(--color-brand-700)] border border-[#c7d2fe] px-2.5 py-1 rounded-[var(--radius-sm)]","children":"Data"}] 36:T4c7,Experience required: 9-14 Yrs Skills: Deep Learning, Machine, Science, Machine learning, Data Science, Big Data, Data

Job Description:

This is a Senior Data Science role, requiring strong hands-on expertise along with leadership capability. The candidate must have experience building and scaling large, production-grade AI/ML systems in complex environments.

The ideal profile should include:

Strong foundation in Machine Learning, Deep Learning and Statistics
Hands-on experience with Python, TensorFlow and PyTorch
Experience working on large-scale data systems and Big Data stack
CI/CD implementation for ML systems
Kubernetes, Docker
MinIO, Trino, Feature Store architecture
GPU computing, CUDA, and NVIDIA stack
Strong SQL expertise
Federated AI architecture knowledge
System design experience focusing on latency, scalability, and observability
Exposure to LLMs and Agentic AI systems

This role requires someone capable of designing and delivering end-to-end AI systems from data engineering and feature design to model deployment, scaling, and monitoring.

34:["$","div",null,{"className":"relative bg-[var(--color-surface)] border border-[var(--color-border)] rounded-[var(--radius-lg)] shadow-[var(--shado