2 Graphics Processing Unit (GPU) Jobs in Hyderabad | Graphics Processing Unit (GPU) Job openings in Hyderabad
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Hyderabad · 4 - 10 years · ₹25L - ₹55L / yr · Posted 28 Oct 2026
Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.
Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.
Key Responsibilities:
Architecture & Platform
- Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
- Lead IaC standards and reusable modules org-wide; own GitOps practices
- Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration
Reliability Engineering
- Define and drive reliability targets (SLOs/SLIs); establish SRE practice
- Lead incident management, RCA, and blameless post-mortems for critical systems
- Partner on infrastructure hardening and compliance (SOC 2, HIPAA)
AI-First Engineering
- Lead AI/ML inference and GPU infrastructure scaling in production
- Evaluate and introduce AI tooling, platforms, and automation best practices
- Contribute to LLM deployment pipelines and AI systems reliability
Leadership & SDLC
- Mentor L1/L2 engineers; influence cross-team infrastructure decisions
- Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
- Evaluate and introduce new tooling and platforms
Key Requirements:
- 4–8 years infrastructure/platform/DevOps/SRE
- Deep expertise in AWS & GCP large-scale production systems
- Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
- AI/ML inference or GPU infrastructure scaling (production track record)
- Strong Terraform / equiv. and GitOps practices
- Python, Go, or Bash scripting and automation
- Track record in scale, reliability, and cost efficiency
- Lead incident response and on-call practices
Nice-to-Have
- LLM Gateway architecture and optimization
- Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
- DevSecOps maturity: SBOM, supply-chain security, policy-as-code
- Open-source contributions or platform-team leadership
Why This Role?
- Build infrastructure and products powering real-world healthcare AI
- Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
- Mission-driven impact — improve patient outcomes and save thousands of staff hours
- High ownership, rapid learning, and significant career upside
- Global collaboration across India and the US
- Seed-stage growth — scale from Seed to Series A alongside the team
- Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering
Bengaluru (Bangalore), Pune, Hyderabad, Delhi, Gurugram, Noida, Ghaziabad, Faridabad, Mumbai, Navi Mumbai, Kolkata, Rajasthan · 5 - 24 years · ₹9L - ₹70L / yr · Profitable · Posted 21 Mar 2025
JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.
Mon-fri role, In office, with excellent perks and benefits!
Position Overview
We are seeking a Software Architect to lead the design and development of high-performance robotics and AI software stacks utilizing NVIDIA technologies. This role will focus on defining scalable, modular, and efficient architectures for robot perception, planning, simulation, and embedded AI applications. You will collaborate with cross-functional teams to build next-generation autonomous systems 9
Key Responsibilities:
1. System Architecture & Design
● Define scalable software architectures for robotics perception, navigation, and AI-driven decision-making.
● Design modular and reusable frameworks that leverage NVIDIA’s Jetson, Isaac ROS, Omniverse, and CUDA ecosystems.
● Establish best practices for real-time computing, GPU acceleration, and edge AI inference.
2. Perception & AI Integration
● Architect sensor fusion pipelines using LIDAR, cameras, IMUs, and radar with DeepStream, TensorRT, and ROS2.
● Optimize computer vision, SLAM, and deep learning models for edge deployment on Jetson Orin and Xavier.
● Ensure efficient GPU-accelerated AI inference for real-time robotics applications.
3. Embedded & Real-Time Systems
● Design high-performance embedded software stacks for real-time robotic control and autonomy.
● Utilize NVIDIA CUDA, cuDNN, and TensorRT to accelerate AI model execution on Jetson platforms.
● Develop robust middleware frameworks to support real-time robotics applications in ROS2 and Isaac SDK.
4. Robotics Simulation & Digital Twins
● Define architectures for robotic simulation environments using NVIDIA Isaac Sim & Omniverse.
● Leverage synthetic data generation (Omniverse Replicator) for training AI models.
● Optimize sim-to-real transfer learning for AI-driven robotic behaviors.
5. Navigation & Motion Planning
● Architect GPU-accelerated motion planning and SLAM pipelines for autonomous robots.
● Optimize path planning, localization, and multi-agent coordination using Isaac ROS Navigation.
● Implement reinforcement learning-based policies using Isaac Gym.
6. Performance Optimization & Scalability
● Ensure low-latency AI inference and real-time execution of robotics applications.
● Optimize CUDA kernels and parallel processing pipelines for NVIDIA hardware.
● Develop benchmarking and profiling tools to measure software performance on edge AI devices.
Required Qualifications:
● Master’s or Ph.D. in Computer Science, Robotics, AI, or Embedded Systems.
● Extensive experience (7+ years) in software development, with at least 3-5 years focused on architecture and system design, especially for robotics or embedded systems.
● Expertise in CUDA, TensorRT, DeepStream, PyTorch, TensorFlow, and ROS2.
● Experience in NVIDIA Jetson platforms, Isaac SDK, and GPU-accelerated AI.
● Proficiency in programming languages such as C++, Python, or similar, with deep understanding of low-level and high-level design principles.
● Strong background in robotic perception, planning, and real-time control.
● Experience with cloud-edge AI deployment and scalable architectures.
Preferred Qualifications
● Hands-on experience with NVIDIA DRIVE, NVIDIA Omniverse, and Isaac Gym
● Knowledge of robot kinematics, control systems, and reinforcement learning
● Expertise in distributed computing, containerization (Docker), and cloud robotics
● Familiarity with automotive, industrial automation, or warehouse robotics
● Experience designing architectures for autonomous systems or multi-robot systems.
● Familiarity with cloud-based solutions, edge computing, or distributed computing for robotics
● Experience with microservices or service-oriented architecture (SOA)
● Knowledge of machine learning and AI integration within robotic systems
● Knowledge of testing on edge devices with HIL and simulations (Isaac Sim, Gazebo, V-REP etc.)


