Senior Robotics Engineer

At InferQ, we are building solutions for autonomous and intelligent aerial systems. We seek a Robotic Navigation Engineer with deep technical rigor and a passion for developing mission-critical navigation, estimation, and path planning systems for UAVs. The role demands hands-on engagement across the autonomy stack. You will work at the intersection of robotics, AI, and aerospace, translating research into reliable field-deployable systems.

Key Responsibilities

• Architect and implement algorithms for joint state estimation, integrating multi-sensor inputs.
• Develop dynamic and real-time path planning solutions for UAVs.
• Create and validate flight simulations using various COTS Simulators or custom HIL/SIL test environments.
• Design and integrate advanced navigation systems.
• Work with avionics, AI, and controls teams to integrate autonomy modules on flight computers and mission systems.
• Conduct flight trials, performance evaluation, and algorithm optimization under real mission conditions.
• Support development of mission-critical autonomy frameworks for UAV systems.

Skillset/ Experience Required

• Strong foundation in linear and nonlinear state estimation and multi-sensor fusion.
• Expertise in path planning and trajectory optimization for aerial platforms.
• Proficiency in C++ / Python and ROS / ROS2 for robotic system development.
• Experience with aerospace kinematics and dynamics modeling, flight control integration, and navigation system design.
• Hands-on experience with Gazebo / X-Plane / AirSim / Unreal Engine simulators.
• Practical understanding of vision-based SLAM, visual odometry, and obstacle avoidance.
• Strong analytical and debugging skills, with a systems-engineering mindset.
• Exposure to AI-based perception systems.
• Integration of algorithms with embedded flight computers.
• Experience with HIL/SIL test setups and flight telemetry systems.
• Familiarity with DO-178C, DO-254, or other lifecycle processes is a plus.

Educational Qualification

• B.E. / B.Tech / M.Tech / Ph.D. in Aerospace, Robotics, Computer Science, Electrical, or related disciplines.
• Academic or project focus in Autonomous Systems, Estimation, Navigation, or AI-based Robotics is preferred.

Technical Lead – Embedded Software Application Projects

link: https://www.ziliconcloud.com/careers

ZILICONCLOUD PRIVATE LIMITED is looking for an experienced Technical Lead with 5–8 years of industry experience in Embedded Systems, IoT, AI, Cloud, and Software Engineering.

The candidate will lead Embedded, IoT, Edge AI, and Cloud projects, define system architecture, convert requirements into technical tasks, and ensure successful project execution and delivery.

Key Responsibilities

• Design modular system architectures for Embedded, IoT, Edge AI, Cloud, REST APIs, and dashboards.
• Convert requirements into clear tasks, milestones, and deliverables.
• Track project progress, manage technical risks, and ensure on-time delivery.
• Guide engineers on coding standards, Git, testing, debugging, and documentation.
• Troubleshoot issues across hardware, firmware, IoT, cloud, backend, and UI.
• Support system integration, testing, debugging, and performance improvement.
• Review technical designs, code, and test results.
• Lead prototype development, integration, technical reviews, and demonstrations.
• Mentor young engineers and explain complex technical concepts in a simple and practical way.
• 
  

Required Skills

C/C++, Python, JavaScript/TypeScript, Linux, FreeRTOS, Microcontrollers, REST APIs, MQTT, Git, Embedded Software, IoT, and system debugging.

Preferred: AWS IoT, Microsoft Azure, ThingsBoard, OpenCV, TensorFlow Lite (TFLite), React, Flutter, or FastAPI.

Education

B.E./B.Tech/M.E./M.Tech in ECE, CSE, Embedded Systems, Mechatronics, or a related field.

📍 Location: East Tambaram, Chennai, Tamil Nadu

💼 Experience: 5–8 Years

🕒 Employment Type: Full-Time

About us

MyRico builds personal AI agents for enterprise, the copilots and digital employees that make humans more productive. The MyRico agents sit at the intersection of enterprise memory, high-end security, and an ever-expanding set of capabilities. We're a small team shipping fast, and the product is live with real customers today.

The role

Full-time · Bangalore

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

What we're looking for

• More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
• Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
• Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
• Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
• Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.

Nice to have

• Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
• Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
• You already orchestrate AI coding agents in your own workflow and have opinions about where they break.

How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

Power Electric Vehicles with embedded software for battery management and autonomous driving.

What you'll do:

• Develop BMS algorithms (SOC/SOH estimation)
• Implement CAN bus communication protocols
• Code motor control algorithms (FOC, sensorless)
• Build ADAS features (ultrasonic parking, vision)
• HIL testing with Vector tools
• Optimize for automotive-grade reliability (AUTOSAR)

What we need:

• C/C++, Embedded Linux/RTOS
• Microcontroller experience (STM32, NXP)
• Control systems or automotive interest
• Debugging skills (oscilloscopes, logic analyzers)

Future-proof skills:

• Work on actual EV prototypes
• Portfolio for Tata, Mahindra EV teams
• Automotive cybersecurity exposure

About the client

They are reimagining video security for the modern world. Their cloud-native platform uses computer vision and AI to help businesses stay safe, make smarter decisions, and move faster—from real-time alerts to seamless clip sharing and multi-site visibility.

You’ll be joining an ambitious, fast-moving team that values clarity, craftsmanship, and impact. Every person here has a voice, ships meaningful work, and helps shape how AI can make the world safer and more connected.

About the Role

We are looking for an Engineering Manager to lead the Core Engineering team in India, working on the systems that power our edge-computing platform.

The team works on technically challenging problems across C++, edge computing, high-concurrency systems, low-latency processing, memory management, and machine-learning workloads running on compute-constrained devices.

This is a hands-on engineering leadership role. You will lead and grow a high-performing team while staying close to architecture, system design, technical decision-making, and critical engineering problems.

As the team scales, you will play a key role in building the engineering organization, raising technical standards, mentoring engineers and managers, and partnering closely with leadership on product and technical strategy.

Responsibilities

Technical Leadership

• Lead the architecture and development of core systems powering our edge-computing platform.
• Drive technical decisions across C++, distributed systems, low-latency and high-concurrency architectures, and resource-constrained environments.
• Review and guide critical architectural and implementation decisions while maintaining strong technical depth.
• Solve complex problems around memory management, performance, reliability, concurrency, and system scalability.
• Work closely with engineers on designing and building production-grade systems running across a fleet of deployed edge devices.
• Guide the deployment and optimization of machine-learning workloads on edge infrastructure.
• Establish strong engineering practices around observability, telemetry, reliability, and performance.

Engineering & People Leadership

• Lead, mentor, and grow a high-performing core engineering team.
• Hire and build the India engineering team as the organization scales.
• Set clear technical and execution standards and create a culture of ownership and accountability.
• Conduct performance reviews, provide regular feedback, and support career development.
• Participate in hiring decisions and build a strong engineering talent pipeline.
• Identify and address performance gaps when required.
• Develop engineers into technical and people leaders as the organization grows.
• Partner with other engineering teams and leadership to align technical execution with company and product goals.

Strategy & Execution

• Own execution for key areas of the core engineering organization and ensure teams deliver reliably against business priorities.
• Participate in product and engineering decision-making, balancing technical quality, speed, reliability, and business impact.
• Work closely with the Head of Engineering and company leadership on technical roadmap and organizational planning.
• Help establish the engineering processes, systems, and team structure required to scale the organization.

Skills & Qualifications

• A Bachelor's or Master's degree in Computer Science
• Around 9+ years of software engineering experience, with meaningful experience leading engineering teams.
• At least 1+ year of engineering management experience, including ownership of people management and performance processes.
• Strong hands-on engineering background in C++ and a deep understanding of systems programming.
• Strong understanding of memory management, concurrency, and performance optimization.
• Experience designing and operating low-latency and high-concurrency systems.
• Experience working with resource-constrained, distributed, edge, IoT, hardware-integrated, or similarly challenging systems.
• Strong understanding of software architecture, distributed systems, and scalable production systems.
• Ability to remain technically hands-on and engage deeply with architecture, code, and complex engineering problems.
• Experience hiring, mentoring, managing performance, and developing engineers.
• Strong communication and collaboration skills, with the ability to influence technical and organizational decisions.
• Comfortable working in a fast-paced, high-ownership startup environment.

Good to Have

• Experience with edge computing or IoT platforms and managing fleets of deployed devices.
• Experience with GPU-based workloads or machine-learning inference at the edge.
• Experience with video processing and streaming, including technologies such as GStreamer.
• Experience with PyTorch or other ML frameworks and integrating ML models into production systems.
• Experience with infrastructure management and automation tools such as Salt.
• Experience with monitoring and observability platforms such as Grafana.
• Experience working with multiple programming languages such as Python, Java, or Shell.

Work Location

Bangalore – HSR Layout

This is a 5-day work-from-office role. We operate with a high level of ownership and flexibility rather than fixed login/logout hours.

What We Offer

• Flexible paid time off and paid holidays
• Early-stage equity in a rapidly growing company
• Referral bonuses
• Regular team off-sites
• Latest Apple products and access to a modern technology stack, including Claude Cowork, Perplexity Computer, Nooks, Clay, Instantly, and more

Why Join Us

We’re on a mission to transform a $50B+ legacy industry by bringing the power of cutting-edge multimodal LLMs and computer vision to real-world security and operations.

From firearm detection to intelligent access control, our AI-native platform turns every camera and sensor into a smart system that enhances safety, efficiency, and awareness.

Founded by ex-Lyft engineers, the company is backed by Ansa Capital, Battery Ventures, Mosaic, 8VC, and Up Partners. The company has raised over $65M and was named to the CB Insights AI 100 as one of the most promising AI companies in the world.

If you're excited about leading a technically exceptional team building mission-critical AI and edge systems that have real-world impact, we'd love to meet you.

About the Role

We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership — from backend AI architecture to frontend user experiences — and can align engineering decisions with measurable product outcomes.

You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.

Example Project

Design and deploy a multi-agent AI system to automate critical stages of a company’s sales cycle, including:

• Generating client proposals using historical SharePoint data and CRM insights
• Summarizing meeting transcripts
• Drafting follow-up communications
• Feeding structured insights into dashboards and workflow tools

The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.

Key Responsibilities

• Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
• Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
• Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
• Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
• Drive architecture decisions balancing scalability, performance, and security
• Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
• Mentor junior engineers and evolve into a broader leadership role as the team grows

Ideal Candidate Profile

Experience Requirements

• 5+ years in full-stack development (Python backend + React/JavaScript frontend)
• Strong experience in API and microservice integration
• 2+ years leading technical teams and coordinating distributed engineering efforts
• 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
• Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions

Technical Expertise

• Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
• Ensuring backend and AI systems are scalable, reliable, observable, and secure
• Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
• Experience building production-grade AI systems within enterprise SaaS ecosystems

We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:

✅ Real-time self-coding based on tasks  

✅ Autonomous multi-agent collaboration  

✅ AI-powered decision-making  

✅ Cross-platform compatibility (Desktop, Web, Mobile)  

We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.

### Responsibilities:

- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)  

- Integrate large language models (GPT-4o, Claude, open-source LLMs)  

- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)  

- Work on real-time task execution pipelines  

- Build cross-platform apps using Electron or Flutter  

- Implement Redis, Vector databases, scalable APIs  

- Guide the architecture of autonomous, self-coding AI systems  

### Must-Have Skills:

- Python (advanced, AI applications)  

- AI/ML experience, including multi-agent orchestration  

- LLM integration knowledge  

- Full-stack development: React or Next.js  

- Redis, Vector Databases (e.g., Pinecone, FAISS)  

- Real-time applications (websockets, event-driven)  

- Cloud deployment (AWS, GCP)  

### Good to Have:

- Experience with code-generation AI models (Codex, GPT-4o coding abilities)  

- Microservices and secure system design  

- Knowledge of AI for workflow automation and productivity tools  

Join us to work on cutting-edge AI technology that builds the future of autonomous software.

Job Description – Mechatronics Engineer

Position

Mechatronics Engineer

Experience

2 years

Location

Bengaluru, India

About the Role

We are looking for a hands-on Mechatronics Engineer with approximately 2 years of experience to work on the development and integration of intelligent electro-mechanical systems.

The role involves a combination of electronics system assembly and testing, sensors and actuators, control algorithms, estimation algorithms, embedded implementation, system configuration, and hardware-software integration. The ideal candidate should be comfortable working across the boundary between mechanical, electrical, embedded software, and algorithms.

Key Responsibilities

1. System Assembly & Integration

• Assemble and integrate electro-mechanical systems, sensors, actuators, embedded computers, controllers, and associated electronics.
• Perform wiring, connection, sensor installation, and basic electrical integration.
• Support integration of cameras, IMUs, GNSS, encoders, motors, servos, and other sensors/actuators.
• Configure systems for laboratory, ground, and flight testing.
• Troubleshoot hardware, electrical, communication, and integration issues.

2. Electronics Testing & Validation

• Develop and execute test procedures for electronic and mechatronic subsystems.
• Perform functional testing, sensor validation, actuator testing, and system-level testing.
• Use laboratory equipment such as oscilloscopes, multimeters, power supplies, electronic loads, and logic analysers.
• Analyse test data and identify hardware, firmware, sensor, or integration issues.
• Maintain test records, test reports, and issue/defect logs.

3. Control & Estimation Algorithms

• Implement and integrate control algorithms for electro-mechanical systems.
• Work with PID, state-space, feedback control, actuator control, and related control techniques.
• Implement estimation algorithms such as complementary filters, Kalman filters, EKF/UKF, or sensor fusion algorithms.
• Perform sensor calibration, parameter estimation, filtering, and system identification.
• Tune control and estimation parameters based on laboratory and flight-test data.

4. Embedded Implementation

• Implement algorithms on embedded processors and real-time computing platforms.
• Interface sensors and actuators using protocols such as UART, SPI, I²C, CAN, RS-232/485, Ethernet, etc.
• Develop or modify embedded C/C++ code for system integration.
• Debug hardware-software interaction and real-time issues.
• Support optimisation and deployment of algorithms on resource-constrained embedded systems.

5. Configuration & Version Management

• Maintain configuration of hardware, firmware, software, sensors, and system parameters.
• Maintain configuration-controlled parameter files, calibration data, firmware versions, and test configurations.
• Use Git or equivalent version-control systems for software and configuration management.
• Maintain proper traceability between hardware configuration, software version, test results, and system performance.
• Support controlled release of system configurations for testing and demonstrations.

6. System Testing & Field Trials

• Participate in system-level integration, laboratory testing, HIL/SIL testing, and field/flight trials.
• Prepare test setups and test cases based on system requirements.
• Collect and analyse telemetry, sensor, actuator, and performance data.
• Diagnose failures during integration and testing and work with the engineering team to resolve them.
• Support verification and validation activities for production-grade systems.

Required Skills

• B.E./B.Tech/M.Tech in Mechatronics, Electronics, Electrical, Instrumentation, Mechanical Engineering, or a related discipline.
• Approximately 2 years of relevant industry/project experience.
• Strong hands-on experience with electronics system assembly, integration, and testing.
• Understanding of sensors, actuators, motors, servos, and embedded systems.
• Good understanding of control systems and estimation/filtering techniques.
• Experience implementing algorithms in C/C++ and/or Python.
• Familiarity with microcontrollers, embedded processors, and real-time systems.
• Working knowledge of communication protocols such as CAN, UART, SPI, I²C and Ethernet.
• Experience using laboratory test equipment such as oscilloscopes and multimeters.
• Familiarity with Git and configuration/version management.
• Ability to read schematics, datasheets, interface specifications, and technical documentation.
• Strong debugging and problem-solving skills.
• Willingness to work hands-on with hardware and participate in field/flight testing.

Good to Have

• Experience with UAVs, robotics, autonomous systems, gimbals, or avionics.
• Experience with IMU, GNSS, magnetometer, barometer, encoder, camera, or other navigation sensors.
• Experience with EKF/UKF, sensor fusion, visual-inertial estimation, or inertial navigation.
• Familiarity with MATLAB/Simulink.
• Experience with PX4, ArduPilot, ROS/ROS2, or similar platforms.
• Experience with HIL/SIL testing.
• Basic understanding of real-time operating systems.
• Experience with hardware bring-up and PCB-level debugging.
• Familiarity with engineering standards, configuration management, and structured V&V processes.

Desired Attributes

• Hands-on engineer who enjoys working with both hardware and software.
• Comfortable moving between mechanical assembly, electronics, algorithms, and embedded implementation.
• Strong debugging mindset with an ability to systematically isolate problems.
• Good understanding of engineering fundamentals rather than dependence on pre-built libraries or tools.
• Able to work independently on assigned modules while collaborating closely with multidisciplinary teams.
• Comfortable working in a fast-paced R&D environment involving prototyping, testing, iteration, and field trials.
• Strong documentation and communication skills.

Typical Technology Environment

Sensors & Actuators: IMU, GNSS, magnetometer, encoders, cameras, motors, servos

Embedded: Microcontrollers, ARM processors, embedded Linux/RTOS

Algorithms: PID, state estimation, Kalman filtering, sensor fusion, system identification

Programming: C/C++, Python, MATLAB/Simulink

Testing: Oscilloscope, logic analyser, multimeter, power supply, HIL/SIL

This is a hands-on R&D engineering role suited for an engineer who wants to work on complete intelligent systems rather than a narrowly defined mechanical or electronics function. The engineer will contribute across assembly → integration → algorithm implementation → configuration → testing → debugging → field validation, with particular emphasis on UAV and autonomous-system applications.

Responsibilities Include:

● Architecting, building, testing, and deploying applications that support our transportation network

● Modifying designs and specifications of complex applications

● Collaborating and adding value through participation in peer code reviews, providing comments and suggestions

● Leverage AWS and other cloud technologies to design and implement systems in a serverless and event-driven environment

● Working with technical and non-technical end-users, other engineers, and product managers in a cross-functional, quick-moving, and collaborative environment

● Analyzing code, requirements, system risks, and software reliability and providing recommendations on how to leverage our technology more efficiently

● Working with Product and Design to confirm requirements, prioritization, and development of new features

● Design and implement LLM-powered features to solve complex logistics challenges, automate manual operational workflows, and unlock new efficiencies for our network.

● Champion AI-assisted engineering practices by integrating machine learning and intelligent automation into our CI/CD pipelines to predict deployment risks and accelerate delivery cycles.

What You Bring:

● Ability to adapt to changing requirements and work in a fast-paced environment.

● Ability to work effectively in a cross-functional team environment.

● 7+ years of experience building, testing and deploying applications in high-traffic production environments

● 7+ years of experience developing software with Javascript, Node.js and React

● Enjoys taking initiative, is a self-starter, willing to move fast and ship quick, and is excited about collaborating on big challenges

Preferred Qualifications:

● Experience in transportation, logistics or network orchestration systems is highly desirable

● Experience working in a remote first environment.

● Proficiency with AWS, GCP, or similar cloud platforms.

● Strong skills in React and Node.js for end-to-end development. 

Position Title: Real-Time Computer Vision & Edge AI Engineer (Founding Engineering Team / Core LLD) 

Reporting Structure: High-Level AI Architect (Principal ML Scientist, Google) 

Domain: Sub-16ms Edge AI, 3D Pose & Shape Estimation (SMPL-X), TensorRT C++ Inference, Zero-Copy Systems 

Performance Benchmark: Hard locked 60 FPS (<16.6 ms total frame budget) on dedicated RTX hardware

1. Position Overview & Architecture 

We are building a proprietary, ultra-low-latency spatial computing platform centered on high-fidelity 100% 3D Digital Twin architecture and real-time human digitization. 

In this role, you will serve as the Low-Level Design (LLD) Core AI Engineer, working directly alongside a Lead AI Scientist from Google. Your primary mandate is to solve complex surface occlusion and volumetric estimation challenges by building an ultra-fast C++ inference pipeline. This system must accurately regress a subject's true underlying 3D body shape and skeletal pose directly from a live camera feed. You will deploy models that extract parametric data (SMPL-X shape/pose parameters) and bridge these joint rotations seamlessly into our Vulkan graphics engine via shared GPU memory.

System Architecture: 

● Hardware Camera Ingestion: (V4L2 / GStreamer / CUDA) 

↓ Raw RGB Frames (Zero CPU Copy) 

● Edge AI Inference: (TensorRT / ONNX C++ API for 3D Pose Tracking, Kinematic Anchoring, SMPL-X Shape) 

↓ 3D Skeletal Transforms & Shape Parameters 

● Zero-Copy Shared Memory: (CUDA-Vulkan Bridge feeding directly into OpenRigLogic / MetaHuman Engine) 

2. Key Responsibilities & Deliverables 

A. Real-Time 3D Pose & Shape Estimation 

● Deploy and optimize state-of-the-art 3D human body reconstruction models (e.g., Shapy, SMPLify-X, CLIFF) to accurately regress the user's underlying skeletal structure and body volume, effectively bypassing unpredictable surface topologies and complex environmental occlusions. 

● Extract mathematically stable shape parameters (β) and pose parameters (θ) to drive the skeletal hierarchy of a high-fidelity digital avatar. 

B. Edge Inference Pipeline (TensorRT) 

● Translate Python-based research models into production-grade C++ inference engines using NVIDIA TensorRT and ONNX Runtime. 

● Implement INT8/FP16 quantization, layer fusion, and custom CUDA plugins to ensure the entire AI inference pass executes within a strict <10 ms budget per frame. 

C. Temporal Smoothing & Anti-Jitter Kinematics

● Implement highly optimized temporal filters (Kalman filters, One-Euro filters, optical flow tracking) in native C++ to eliminate all high-frequency jitter from the output joint rotations before they reach the graphics engine. 

● Ensure kinematic constraints (e.g., fixed bone lengths) are strictly maintained to prevent the digital asset from stretching or warping dynamically. 

D. Zero-Copy Ingestion & Engine Synchronization 

● Build hardware-accelerated video capture pipelines using V4L2 or GStreamer to ingest raw camera frames directly into GPU memory. 

● Bridge the output coordinate data and transformation matrices to the graphics team using POSIX shared memory and CUDA-Vulkan interop (VK_KHR_external_memory_fd), eliminating CPU staging overhead. 

3. Technical Qualifications & Tech Stack 

● Core Programming: Production-level Modern C++ (C++17/20), Python (strictly for model training/validation), and CUDA C/C++. 

● AI & Acceleration Frameworks: NVIDIA TensorRT, ONNX Runtime (C++ API), PyTorch. 

● Computer Vision Libraries: OpenCV (CUDA backend), MediaPipe C++ bindings. 

● Mathematical Foundations: 3D Kinematics, Matrix Transformations, Quaternions/Euler angles, statistical body modeling (SMPL/SMPL-X architecture). 

● Systems Architecture: Low-latency memory management, multi-threading (std::jthread, lock-free queues), SIMD vectorization. 

4. Relevant Projects & Demonstrable Experience (Preferred) 

Candidates will be preferred if they present functional codebases, GitHub repositories, or thesis work covering:

● Real-Time Body Fitting / Pose Estimation: Practical experience deploying 3D human pose or shape reconstruction models on live video feeds. 

● TensorRT / C++ Deployment: Demonstrable experience stripping a PyTorch model out of Python and running it natively in C++ using TensorRT or ONNX, ideally with custom CUDA layers or INT8 calibration. 

● High-Throughput Vision Pipelines: Built a C++ video processing pipeline that aggressively minimizes latency and avoids memory garbage collection pauses. 

● Kinematics & Smoothing: Applied mathematical filters to raw sensor or AI data to produce smooth, mechanically accurate 3D rotations. 

5. Compensation & Engagement Structure 

● Compensation: ₹1,50,000 to ₹2,00,000/month 

● Mentorship: Direct architectural guidance, algorithm review, and technical leadership from a Principal ML Scientist at Google. 

● Hardware: Dedicated high-end workstation equipped with discrete NVIDIA RTX hardware.