Telangana Embedded ml engineer – edge accelerator Jobs – 7 Open Jobs Today

Embedded ML Engineer – Edge Accelerator
Eurth Techtronics —Hyderabad, Telangana
- Full-time
- Computer Science
- Master's degree
- C++
Senior Staff Engineer-C++ , Embedded, AI/ML, GenAI,edge aing
Qualcomm —Hyderabad, Telangana
- Remote
- Doctoral degree
- Computer Science
- Engineering
Engineer- ML tools
Qualcomm —Hyderabad, Telangana
- Doctoral degree
- Computer Science
- Engineering
LPAI ML SW Senior Engineer
Qualcomm —Hyderabad, Telangana
- Doctoral degree
- Computer Science
- Engineering
Embedded Software Engineer – Edge AI Inference
Eurth Techtronics —Hyderabad, Telangana
- Full-time
- Master's degree
- C++
- Bachelor's degree
[India] Embedded Automation & QA Engineer
EdgeCortix —Hyderabad, Telangana
- Full-time
- Computer Science
- Software troubleshooting
- Research
Quick apply
Embedded Systems Architect – Edge AI Hardware
Eurth Techtronics —Hyderabad, Telangana
- Full-time
- System design
- Master's degree
- C++

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Embedded ML Engineer – Edge Accelerator

Eurth Techtronics -
Hyderabad, Telangana

Apply Now

Job details

Full-time

Qualifications

TensorFlow
Computer Science
Signal processing
5G
Encryption
Firmware
Git
Master's degree
C++
Docker
C
Bachelor's degree
Machine learning
Embedded software
SDKs
Scripting
GitHub
B.E.
Linux
Manufacturing
AI
Python

Full job description

Hyderabad, Telangana, India

Job Type

Full Time

Workspace

About the Role

About the Role
We are seeking a passionate and skilled Embedded ML Engineer to work on cutting-edge ML inference pipelines for low-power, real-time embedded platforms. You will help design and deploy highly efficient ML models on custom hardware accelerators like Hailo, Coral (Edge TPU), Kendryte K210, and Torrent/BlackHole in real-world IoT systems.

This role combines model optimization, embedded firmware development, and toolchain management. You will be responsible for translating large ML models into efficient quantized versions, benchmarking them on custom hardware, and integrating them with embedded firmware pipelines that interact with real-world sensors and peripherals.

Requirements

Key Responsibilities

ML Model Optimization & Conversion

Convert, quantize, and compile models built in TensorFlow, PyTorch, or ONNX to hardware-specific formats.
Work with compilers and deployment frameworks like TFLite, HailoRT, EdgeTPU Compiler, TVM, or ONNX Runtime.
Use techniques such as post-training quantization, pruning, distillation, and model slicing.

Embedded Integration & Inference Deployment

Integrate ML runtimes in C/C++ or Python into firmware stacks built on RTOS or embedded Linux.
Handle real-time sensor inputs (camera, accelerometer, microphone) and pass them through inference engines.
Manage memory, DMA transfers, inference buffers, and timing loops for deterministic behavior.

Benchmarking & Performance Tuning

Profile and optimize models for latency, memory usage, compute load, and power draw.
Work with runtime logs, inference profilers, and vendor SDKs to squeeze maximum throughput on edge hardware.
Conduct accuracy vs performance trade-off studies for different model variants.

Testing & Validation

Design unit, integration, and hardware-in-loop (HIL) tests to validate model execution on actual devices.
Collaborate with hardware and firmware teams to debug runtime crashes, inference failures, and edge cases.
Build reproducible benchmarking scripts and test data pipelines.

Required Qualifications

Education:

BE/B.Tech/M.Tech in Electronics, Embedded Systems, Computer Science, or related disciplines.

Experience:

2–4 years in embedded ML, edge AI, or firmware development with ML inference integration.

Technical Skills Required

Embedded Firmware & Runtime

Strong experience in C/C++, basic Python scripting.
Experience with RTOS (FreeRTOS, Zephyr) or embedded Linux.
Understanding of memory-mapped I/O, ring buffers, circular queues, and real-time execution cycles.

ML Model Toolchains

Experience with TensorFlow Lite, ONNX Runtime, HailoRT, EdgeTPU, uTensor, or TinyML.
Knowledge of quantization-aware training or post-training quantization techniques.
Familiarity with model conversion pipelines and hardware-aware model profiling.

Media & Sensor Stack

Ability to work with input/output streams from cameras, IMUs, microphones, etc.
Experience integrating inference with V4L2, GStreamer, or custom ISP preprocessors is a plus.

Tooling & Debugging

Git, Docker, cross-compilation toolchains (Yocto, CMake).
Debugging with SWD/JTAG, GDB, or serial console-based logging.
Profiling with memory maps, timing charts, and inference logs.

Preferred (Bonus) Skills

Previous work with low-power vision devices, audio keyword spotting, or sensor fusion ML.
Familiarity with edge security (encrypted models, secure firmware pipelines).
Hands-on with simulators/emulators for ML testing (Edge Impulse, Hailo’s HEF emulator, etc.).
Participation in TinyML forums, open-source ML toolkits, or ML benchmarking communities.

Why Join Us?

At EURTH TECHTRONICS PVT LTD, we're not just building IoT firmware—we're deploying machine learning intelligence on ultra-constrained edge platforms, powering real-time decisions at the edge.

Get exposure to full-stack embedded ML pipelines — from model quantization to runtime integration. Work with a world-class team focused on ML efficiency, power optimization, and embedded system scalability. Contribute to mission-critical products used in industrial automation, medical wearables, smart infrastructure, and more.

How to Apply

Send your updated resume + GitHub/portfolio links to: [email protected]

About the Company

About EURTH TECHTRONICS PVT LTD
EURTH TECHTRONICS PVT LTD is a cutting-edge Electronics Product Design and Engineering firm specializing in embedded systems, IoT solutions, and high-performance hardware development. We provide end-to-end product development services—from PCB design, firmware development, and system architecture to manufacturing and scalable deployment.

With deep expertise in embedded software, signal processing, AI-driven edge computing, RF communication, and ultra-low-power design, we build next-generation industrial automation, consumer electronics, and smart infrastructure solutions.

Our Core Capabilities
Embedded Systems & Firmware Engineering – Architecting robust, real-time embedded solutions with RTOS, Linux, and MCU/SoC-based firmware.
IoT & Wireless Technologies – Developing LoRa, BLE, Wi-Fi, UWB, and 5G-based connected solutions for industrial and smart city applications.
Hardware & PCB Design – High-performance PCB layout, signal integrity optimization, and design for manufacturing (DFM/DFA).
Product Prototyping & Manufacturing – Accelerating concept-to-market with rapid prototyping, design validation, and scalable production.
AI & Edge Computing – Implementing real-time AI/ML on embedded devices for predictive analytics, automation, and security.
Security & Cryptography – Integrating post-quantum cryptography, secure boot, and encrypted firmware updates.

Our Industry Impact
✅ IoT & Smart Devices – Powering the next wave of connected solutions for industrial automation, logistics, and smart infrastructure.
✅ Medical & Wearable Tech – Designing low-power biomedical devices with precision sensor fusion and embedded intelligence.
✅ Automotive & Industrial Automation – Developing AI-enhanced control systems, predictive maintenance tools, and real-time monitoring solutions.
✅ Scalable Enterprise & B2B Solutions – Delivering custom embedded hardware and software tailored to OEMs, manufacturers, and system integrators.

Our Vision
We are committed to advancing technology and innovation in embedded product design. With a focus on scalability, security, and efficiency, we empower businesses with intelligent, connected, and future-ready solutions.

We currently cater to B2B markets, offering customized embedded development services, with a roadmap to expand into direct-to-consumer (B2C) solutions.

Apply Now

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embedded ml engineer – edge accelerator jobs in telangana

Embedded ML Engineer – Edge Accelerator

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