361 Onnx Jobs - Page 7

Expected Notice Period : 15 Days Shift : (GMT+01:00) Europe/London (BST) Opportunity Type : Remote Placement Type: Full Time Contract for 6 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - UK's Leading AgriTech Company) What do you need for this opportunity? Must have skills required: AgriTech Industry, Large Language Models, Nvidia Jetson, Raspberry Pi, Blender, Computer Vision, OpenCV, Python, Pytorch/tensorflow, Segmentation, Extraction, Regression UK's Leading AgriTech Company is Looking for: Location: Remote Type: 6 months contract Experience Level : 35 Years Industry: Agritech | Sustainability | AI for Renewables About Us We're an AI-first company transforming the renewable and sustainable agriculture space. Our mission is to harness advanced computer vision and machine learning to enable smart, data-driven decisions in the livestock and agricultural ecosystem. We focus on practical applications such as automated weight estimation of cattle , livestock monitoring, and resource optimization to drive a more sustainable food system. Role Overview We are hiring a Computer Vision Engineer to develop intelligent image-based systems for livestock management, focusing on cattle weight estimation from images and video feeds. You will be responsible for building scalable vision pipelines, working with deep learning models, and bringing AI to production in real-world farm settings . Key Responsibilities Design and develop vision-based models to predict cattle weight from 2D/3D images, video, or depth data. Build image acquisition and preprocessing pipelines using multi-angle camera data. Implement classical and deep learning-based feature extraction techniques (e.g., body measurements, volume estimation). Conduct camera calibration, multi-view geometry analysis, and photogrammetry for size inference. Apply deep learning architectures (e.g., CNNs, ResNet, UNet, Mask R-CNN) for object detection, segmentation, and keypoint localization. Build 3D reconstruction pipelines using stereo imaging, depth sensors, or photogrammetry. Optimize and deploy models for edge devices (e.g., NVIDIA Jetson) or cloud environments. Collaborate with data scientists and product teams to analyze livestock datasets, refine prediction models, and validate outputs. Develop tools for automated annotation, model training pipelines, and continuous performance tracking. Required Qualifications & Skills Computer Vision: Object detection, keypoint estimation, semantic/instance segmentation, stereo imaging, and structure-from-motion. Weight Estimation Techniques: Experience in livestock monitoring, body condition scoring, and volumetric analysis from images/videos. Image Processing: Noise reduction, image normalization, contour extraction, 3D reconstruction, and camera calibration. Data Analysis & Modeling: Statistical modeling, regression techniques, and feature engineering for biological data. Technical Stack Programming Languages: Python (mandatory) Libraries & Frameworks: OpenCV, PyTorch, TensorFlow, Keras, scikit-learn 3D Processing: Open3D, PCL (Point Cloud Library), Blender (optional) Data Handling: NumPy, Pandas, DVC Annotation Tools: LabelImg, CVAT, Roboflow Cloud & DevOps: AWS/GCP, Docker, Git, CI/CD pipelines Deployment Tools: ONNX, TensorRT, FastAPI, Flask (for model serving) Preferred Qualifications Prior experience working in agritech, animal husbandry, or precision livestock farming. Familiarity with Large Language Models (LLMs) and integrating vision + language models for domain-specific insights. Knowledge of edge computing for on-farm device deployment (e.g., NVIDIA Jetson, Raspberry Pi). Contributions to open-source computer vision projects or relevant publications in CVPR, ECCV, or similar conferences. Soft Skills Strong problem-solving and critical thinking skills Clear communication and documentation practices Ability to work independently and collaborate in a remote, cross-functional team Why Join Us? Work at the intersection of AI and sustainability Be part of a dynamic and mission-driven team Opportunity to lead innovation in an emerging field of agritech Flexible remote work environment

Overview: WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Responsibilities: MTS SOFTWARE DEVELOPMENT ENG INEER THE ROLE: AMD is looking for a specialized software engineer who is passionate about improving the performance of key applications and benchmarks . You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology. THE PERSON: The ideal candidate should be passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD. Key Responsibilities Develop test cases to validate functionality and performance. Monitor and maintain end-to-end ML test cases for the compiler in production, addressing issues as they arise. Contribute to open-source projects, sharing your developments with the community. Influence the direction of the AMD AI platform. Collaborate across teams with various groups and stakeholders. Preferred Experience A minimum of 7+ years of experience in relevant fields. Proficiency with AI/DL frameworks such as PyTorch, ONNX, or TensorFlow. Exceptional programming skills in Python, including debugging, profiling, and performance analysis. Experience with machine learning pipelines and CI/CD pipelines. Knowledge of MLIR is a significant advantage. Strong communication and problem-solving abilities. KEY RESPONSIBILITIES: Work with AMD’s architecture specialists to improve future products Apply a data minded approach to target optimization efforts Stay informed of software and hardware trends and innovations, especially pertaining to algorithms and architecture Design and develop new groundbreaking AMD technologies Participating in new ASIC and hardware bring ups Debugging/fix existing issues and research alternative, more efficient ways to accomplish the same work Develop technical relationships with peers and partners #LI-NR1 Qualifications: Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

Overview We are hiring a Machine Learning Engineer with strong experience in Computer Vision , Natural Language Processing (NLP) , and Backend Development . You’ll be responsible for training and deploying deep learning models, implementing research papers, and building production-ready APIs using Flask, FastAPI, or Django. Key Responsibilities Develop ML/DL models for: Computer Vision : classification, object detection, segmentation. NLP : text classification, NER, summarization. Implement research papers and build production-ready prototypes. Use libraries such as PyTorch , OpenCV , Pillow , TorchVision , and Transformers . Optimize models with techniques like quantization , pruning , ONNX export , and TorchScript . Build and deploy RESTful APIs using FastAPI , Flask , or Django . Containerize applications using Docker and deploy them to cloud or local servers. Write clean, efficient, and scalable code for backend and ML pipelines. Required Skills Solid understanding of Machine Learning and Deep Learning . Experience with: PyTorch , OpenCV , Pillow Computer Vision (detection, segmentation, classification) NLP libraries like Hugging Face Transformers , spaCy , NLTK Strong backend skills using FastAPI , Flask , or Django . Familiar with Docker , Git , and Linux environments. Experience with model deployment and optimization tools (ONNX, TorchScript). Nice to Have Knowledge of Generative AI / LLMs Experience with ONNX , TensorRT , or TorchScript MLOps tools: MLflow , DVC , Airflow Experience with Cloud platforms (AWS, GCP, Azure) Qualifications Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or a related field. Job Type: Full-time Pay: ₹272,876.24 - ₹1,548,746.18 per year Schedule: Evening shift Monday to Friday Work Location: In person

Company Description Echoleads.ai leverages AI-powered sales agents to engage, qualify, and convert leads through real-time voice conversations. Our voice bots act as scalable sales representatives, making thousands of smart, human-like calls daily to follow up instantly, ask the right questions, and book appointments effortlessly. Echoleads integrates seamlessly with lead sources like Meta Ads, Google Ads, and CRMs, ensuring leads are never missed. Serving modern sales and marketing teams across various industries, our AI agents proficiently handle outreach, lead qualification, and appointment setting. About the Role: We are seeking a highly experienced Voice AI /ML Engineer to lead the design and deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker diarization, wake word detection, and building production-grade modular audio processing pipelines to power next-generation contact center solutions, intelligent voice agents, and telecom-grade audio systems. You will work at the intersection of deep learning, streaming infrastructure, and speech/NLP technology, creating scalable, low-latency systems across diverse audio formats and real-world applications. Key Responsibilities: Voice & Audio Intelligence: Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for real-time transcription. Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for lifelike voice generation and cloning. Implement speaker diarization for segmenting and identifying speakers in multi-party conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral clustering). Design robust wake word detection models with ultra-low latency and high accuracy in noisy conditions. Real-Time Audio Streaming & Voice Agent Infrastructure: Architect bi-directional real-time audio streaming pipelines using WebSocket, gRPC, Twilio Media Streams, or WebRTC. Integrate voice AI models into live voice agent solutions, IVR automation, and AI contact center platforms. Optimize for latency, concurrency, and continuous audio streaming with context buffering and voice activity detection (VAD). Build scalable microservices to process, decode, encode, and stream audio across common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4). Deep Learning & NLP Architecture: Utilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for speech and language tasks. Implement end-to-end pipelines including text normalization, G2P mapping, NLP intent extraction, and emotion/prosody control. Fine-tune pre-trained language models for integration with voice-based user interfaces. Modular System Development: Build reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming inference, and data augmentation. Design APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with format conversions and buffering. Develop performance benchmarks and optimize for CPU/GPU, memory footprint, and real-time constraints. Engineering & Deployment: Writing robust, modular, and efficient Python code Experience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP) Optimize models for real-time inference using ONNX, TorchScript, and CUDA, including quantization, context-aware inference, model caching. On device voice model deployment.

Key Responsibilities: Design and optimize model serving infrastructure with a focus on low latency and cost efficiency Build scalable inference pipelines across different hardware acceleration options Implement monitoring and observability solutions for ML systems Collaborate with ML Engineers to define best practices for deployment Develop enterprise-grade, cost-efficient ML solutions Work closely with MLEs, QA, and DevOps teams in a distributed environment Evaluate new technologies and contribute to system architecture decisions Drive continuous improvements in ML infrastructure Required Experience & Skills: 5+ years of experience in software engineering using Python Hands-on experience with ML frameworks (especially PyTorch) Experience optimizing ML models using hardware accelerators (e.g., AWS Neuron, ONNX, TensorRT) Familiarity with AWS ML services and hardware-accelerated compute (e.g., SageMaker, Inferentia, Trainium) Proven ability to build and maintain serverless architectures on AWS Strong understanding of event-driven patterns (SQS/SNS) and caching strategies Proficiency with Docker and container orchestration tools Solid grasp of RESTful API design and implementation Focus on secure, high-quality code with experience using static code analysis tools Strong problem-solving, algorithmic thinking, and communication skills

Hyderabad, Telangana, India Job Type Full Time About the Role About the Role We are seeking a highly skilled and visionary Senior Embedded Systems Architect to lead the design and implementation of next-generation AI-powered embedded platforms. This role demands deep technical proficiency across embedded systems, AI model deployment, hardware–software co-design, and media-centric inference pipelines. You will architect full-stack embedded AI solutions using custom AI accelerators such as Google Coral (Edge TPU), Hailo, BlackHole (Torrent), and Kendryte, delivering real-time performance in vision, audio, and multi-sensor edge deployments. The ideal candidate brings a combination of system-level thinking, hands-on prototyping, and experience in optimizing AI workloads for edge inference. This is a high-impact role where you will influence product architecture, ML tooling, hardware integration, and platform scalability for a range of IoT and intelligent device applications. Requirements Key Responsibilities ️ System Architecture & Design Define and architect complete embedded systems for AI workloads — from sensor acquisition to real-time inference and actuation . Design multi-stage pipelines for vision/audio inference: e.g., ISP preprocessing CNN inference postprocessing. Evaluate and benchmark hardware platforms with AI accelerators (TPU/NPU/DSP) for latency, power, and throughput. Edge AI & Accelerator Integration Work with Coral, Hailo, Kendryte, Movidius, and Torrent accelerators using their native SDKs (EdgeTPU Compiler, HailoRT, etc.). Translate ML models (TensorFlow, PyTorch, ONNX) for inference on edge devices using cross-compilation , quantization , and toolchain optimization . Lead efforts in compiler flows such as TVM, XLA, Glow, and custom runtime engines. ️ Media & Sensor Processing Pipelines Architect pipelines involving camera input , ISP tuning , video codecs , audio preprocessors , or sensor fusion stacks . Integrate media frameworks such as V4L2 , GStreamer , and OpenCV into real-time embedded systems. Optimize for frame latency, buffering, memory reuse, and bandwidth constraints in edge deployments. ️ Embedded Firmware & Platform Leadership Lead board bring-up, firmware development (RTOS/Linux), peripheral interface integration, and low-power system design. Work with engineers across embedded, AI/ML, and cloud to build robust, secure, and production-ready systems. Review schematics and assist with hardware–software trade-offs, especially around compute, thermal, and memory design. Required Qualifications ‍ Education: BE/B.Tech/M.Tech in Electronics, Electrical, Computer Engineering, Embedded Systems, or related fields. Experience: Minimum 5+ years of experience in embedded systems design. Minimum 3 years of hands-on experience with AI accelerators and ML model deployment at the edge. Technical Skills Required Embedded System Design Strong C/C++, embedded Linux, and RTOS-based development experience. Experience with SoCs and MCUs such as STM32, ESP32, NXP, RK3566/3588, TI Sitara, etc. Cross-architecture familiarity: ARM Cortex-A/M, RISC-V, DSP cores. ML & Accelerator Toolchains Proficiency with ML compilers and deployment toolchains: ONNX, TFLite, HailoRT, EdgeTPU compiler, TVM, XLA . Experience with quantization , model pruning , compiler graphs , and hardware-aware profiling . Media & Peripherals Integration experience with camera modules , audio codecs , IMUs , and other digital/analog sensors . Experience with V4L2 , GStreamer , OpenCV , MIPI CSI , and ISP tuning is highly desirable. System Optimization Deep understanding of compute budgeting , thermal constraints , memory management , DMA , and low-latency pipelines . Familiarity with debugging tools: JTAG , SWD , logic analyzers , oscilloscopes , perf counters , and profiling tools. Preferred (Bonus) Skills Experience with Secure Boot , TPM , Encrypted Model Execution , or Post-Quantum Cryptography (PQC) . Familiarity with safety standards like IEC 61508 , ISO 26262 , UL 60730 . Contributions to open-source ML frameworks or embedded model inference libraries. Why Join Us? At EURTH TECHTRONICS PVT LTD , you won't just be optimizing firmware — you will architect full-stack intelligent systems that push the boundary of what's possible in embedded AI. Work on production-grade, AI-powered devices for industrial, consumer, defense, and medical applications . Collaborate with a high-performance R&D team that builds edge-first, low-power, secure, and scalable systems . Drive core architecture and set the technology direction for a fast-growing, innovation-focused organization. How to Apply Send your updated resume + GitHub/portfolio links to: jobs@eurthtech.com 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.

Hyderabad, Telangana, India Job Type Full Time About the Role About the Role We are looking for a hands-on and technically proficient Embedded Software Team Lead to drive the development of intelligent edge systems that combine embedded firmware, machine learning inference, and hardware acceleration. This role is perfect for someone who thrives at the intersection of real-time firmware design, AI model deployment, and hardware-software co-optimization. You will lead a team delivering modular, scalable, and efficient firmware pipelines that run quantized ML models on accelerators like Hailo, Coral, Torrent (BlackHole), Kendryte, and other emerging chipsets. Your focus will include model runtime integration, low-latency sensor processing, OTA-ready firmware stacks, and CI/CD pipelines for embedded products at scale Requirements Key Responsibilities Technical Leadership & Planning Own the firmware lifecycle across multiple AI-based embedded product lines. Define system and software architecture in collaboration with hardware, ML, and cloud teams. Lead sprint planning, code reviews, performance debugging, and mentor junior engineers. ️ ML Model Deployment & Runtime Integration Collaborate with ML engineers to port, quantize, and deploy models using TFLite , ONNX , or HailoRT . Build runtime pipelines that connect model inference with real-time sensor data (vision, IMU, acoustic). Optimize memory and compute flows for edge model execution under power/bandwidth constraints. Firmware Development & Validation Build production-grade embedded stacks using RTOS (FreeRTOS/Zephyr) or embedded Linux . Implement secure bootloaders, OTA update mechanisms, and encrypted firmware interfaces. Interface with a variety of peripherals including cameras, IMUs, analog sensors, and radios (BLE/Wi-Fi/LoRa). ️ CI/CD, DevOps & Tooling for Embedded Set up and manage CI/CD pipelines for firmware builds, static analysis, and validation. Integrate Docker-based toolchains, hardware-in-loop (HIL) testing setups, and simulators/emulators. Ensure codebase quality, maintainability, and test coverage across the embedded stack. Required Qualifications ‍ Education: BE/B.Tech/M.Tech in Embedded Systems, Electronics, Computer Engineering, or related fields. Experience: Minimum 4+ years of embedded systems experience. Minimum 2 years in a technical lead or architect role. Hands-on experience in ML model runtime optimization and embedded system integration. Technical Skills Required Embedded Development & Tools Expert-level C/C++ , hands-on with RTOS and Yocto-based Linux . Proficient with toolchains like GCC/Clang, OpenOCD, JTAG/SWD, Logic Analyzers. Familiarity with OTA , bootloaders , and memory management (heap/stack analysis, linker scripts). ML Model Integration Proficiency in TFLite , ONNX Runtime , HailoRT , or EdgeTPU runtimes . Experience with model conversion, quantization (INT8, FP16), runtime optimization. Ability to read/modify model graphs and connect to inference APIs. Connectivity & Peripherals Working knowledge of BLE, Wi-Fi, LoRa, RS485 , USB, and CAN protocols. Integration of camera modules , MIPI CSI , IMUs , and custom analog sensors . ️ DevOps for Embedded Hands-on with GitLab/GitHub CI, Docker, and containerized embedded builds. Build system expertise: CMake , Make , Bazel , or Yocto preferred. Experience in automated firmware testing (HIL, unit, integration). Preferred (Bonus) Skills Familiarity with machine vision pipelines , ISP tuning , or video/audio codec integration . Prior work on battery-operated devices , energy-aware scheduling , or deep sleep optimization . Contributions to embedded ML open-source projects or model deployment tools. Why Join Us? At EURTH TECHTRONICS PVT LTD , we go beyond firmware—we’re designing and deploying embedded intelligence on every device, from industrial gateways to smart consumer wearables. Build and lead teams working on cutting-edge real-time firmware + ML integration . Work on full-stack embedded ML systems using the latest AI accelerators and embedded chipsets . Drive product-ready, scalable software platforms that power IoT, defense, medical , and consumer electronics . How to Apply Send your updated resume + GitHub/portfolio links to: jobs@eurthtech.com 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.

Hyderabad, Telangana, India Job Type Full Time 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: jobs@eurthtech.com 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.

hiring a Machine Learning / Deep Learning Engineer with DevOps and MLOps experience: Job Title: Machine Learning / Deep Learning Engineer (2+ Years Experience) Location: Gurugram / Delhi NCR (Work from Office Preferred) Experience: Minimum 2 years in ML/DL & MLOps Job Type: Full-Time About the Role We are looking for a passionate and skilled ML/DL Engineer with strong experience in MLOps, FastAPI, Kubernetes , and DevOps practices . If you love building scalable AI systems and deploying them into real-world environments, we’d love to meet you. You’ll work closely with our product, research, and backend teams to deploy end-to-end AI pipelines and models. Key Responsibilities Design, develop, and deploy ML/DL models using Python, FastAPI, and related frameworks Implement scalable MLOps pipelines using tools like Docker, Kubernetes, and CI/CD Optimize model serving and monitor model performance in production Collaborate with data scientists and backend developers to integrate models into production systems Build robust APIs using FastAPI or Django for model inference Apply DevOps best practices for versioning, testing, and deployment Work on AI solutions across Computer Vision, NLP, and classic ML algorithms Required Skills 2+ years of hands-on experience in Machine Learning / Deep Learning Solid experience with MLOps tools , containerization (Docker), and orchestration ( Kubernetes ) Proficiency in FastAPI and Python Working knowledge of DevOps , CI/CD (GitHub Actions, Jenkins, etc.) Familiarity with Django and model deployment Experience with Computer Vision , Natural Language Processing , and ML algorithms Solid understanding of model evaluation, optimization, and scalability Nice to Have Experience with cloud platforms (AWS, GCP, or Azure) Kubernetes and fast API Familiarity with ONNX, TensorFlow Serving, or TorchServe Contributions to open-source or past projects in production Preferred Candidate Location Gurugram / Delhi NCR preferred (In-office role) A Job Types: Full-time, Permanent Pay: ₹35,000.00 - ₹50,000.00 per month Work Location: In person

About the Role: We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Required Skills & Qualifications: Technical Skills 5+ Years of Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models. What do you get in return? Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks : Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats : Dive into our casual "Growth Chats" where you can learn from the best whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone: Stay fueled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards : We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications: We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications .

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Machine Learning Engineer Job Location: Hyderabad More details below: Join a new and growing team at Qualcomm focused on advancing state-of-the-art in Machine Learning. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities. See your work directly impact billions of mobile devices around the world. In this position, you will be responsible for the development and commercialization of ML solutions like Snapdragon Neural Processing Engine (SNPE) and AI Model Efficiency Toolkit (AIMET) on Qualcomm SoCs. You will have expert knowledge of design, improvement, and maintenance of large AI software stacks using best practices. Work Experience: 1. 8-12 years of relevant work experience in software development 2. Live and breathe quality software development with excellent analytical and debugging skills. Strong understanding of Deep Learning and Machine learning theory and practice. 3. Experience with Deep learning model development. Data transformations, model training, model design, model optimization. 4. Familiarity with various deep learning architectures and problem domains like Computer Vision, Speech recognition, NLP etc. 5. Strong development skills in Python and C++. Experience with at least one machine learning framework like TensorFlow, ONNX, Pytorch, etc. 6. Understanding of software development and debugging in embedded environments. 7. Excellent communication skills (verbal, presentation, written) 8. Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications 1. Familiarity with neural network operators and model formats including PyTorch, ONNX, and Tensorflow. 2. Familiarity with neural network optimization techniques like graph optimization, quantization, pruning, knowledge distillation, network architecture search etc. 3. Strong understanding about embedded systems, system design fundamentals. 4. Well versed in version control tools like git 5. Experience with machine learning accelerators, optimizing algorithms for hardware acceleration cores, working with heterogeneous or parallel computing systems. Educational Requirements Bachelor's/Master’s/PhD in Computer Science, Computer Engineering, or Electrical Engineering

About the Role We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Type: Full-time Pay: ₹2,000,000.01 - ₹3,002,234.14 per year Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person

About DeepTek DeepTek is a pioneering healthcare AI company aiming to transform radiology by empowering radiologists with an AI-powered, feature-rich radiology platform and specialized AI models. We leverage cutting-edge technologies to deliver advanced solutions in medical imaging. With a team of over 200+ members, including top-tier application developers, data scientists, and expert radiologists, DeepTek fosters an environment of innovation and collaboration. Job Description We are looking for a Data Scientist who is passionate about working in the healthcare AI domain. This role will involve collaborating with cross-functional teams, including senior data scientists, application developers, and radiology experts, to develop and refine AI solutions for medical imaging. You will gain hands-on experience working on advanced projects and research opportunities in Computer Vision and Deep Learning. Key Responsibilities Develop and optimize deep learning models for medical image analysis, including segmentation, classification, and object detection. Preprocess and clean medical imaging datasets to enhance AI model performance and reliability. Conduct model evaluation, error analysis, and performance benchmarking to improve accuracy and generalization. Collaborate with radiologists and domain experts to refine AI model outputs and ensure clinical relevance. Experience 2-3 years Data Science/Machine Learning experience Required Skills Strong fundamental knowledge of machine learning, computer vision and image processing Demonstrable experience training convolutional neural networks for segmentation and object detection Strong programming skills in Python and familiarity with data science and image processing libraries (e.g., NumPy, pandas, scikit-learn, opencv, PIL). Hands-on experience with deep learning frameworks like Keras or PyTorch. Experience with model evaluation and error analysis. Desired Skills Familiarity with healthcare or radiology datasets. Familiarity with ONNX format Qualification Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field. Company Location Baner, Pune, India https://goo.gl/maps/Fmd22UNSiXYQD2ba9 Please send your resumes at hr@deeptek.ai

Hyderabad, Telangana, India Job Type Full Time About the Role About the Role We are seeking a highly skilled and visionary Senior Embedded Systems Architect to lead the design and implementation of next-generation AI-powered embedded platforms. This role demands deep technical proficiency across embedded systems, AI model deployment, hardware–software co-design, and media-centric inference pipelines. You will architect full-stack embedded AI solutions using custom AI accelerators such as Google Coral (Edge TPU), Hailo, BlackHole (Torrent), and Kendryte, delivering real-time performance in vision, audio, and multi-sensor edge deployments. The ideal candidate brings a combination of system-level thinking, hands-on prototyping, and experience in optimizing AI workloads for edge inference. This is a high-impact role where you will influence product architecture, ML tooling, hardware integration, and platform scalability for a range of IoT and intelligent device applications. Requirements Key Responsibilities ️ System Architecture & Design Define and architect complete embedded systems for AI workloads — from sensor acquisition to real-time inference and actuation . Design multi-stage pipelines for vision/audio inference: e.g., ISP preprocessing CNN inference postprocessing. Evaluate and benchmark hardware platforms with AI accelerators (TPU/NPU/DSP) for latency, power, and throughput. Edge AI & Accelerator Integration Work with Coral, Hailo, Kendryte, Movidius, and Torrent accelerators using their native SDKs (EdgeTPU Compiler, HailoRT, etc.). Translate ML models (TensorFlow, PyTorch, ONNX) for inference on edge devices using cross-compilation , quantization , and toolchain optimization . Lead efforts in compiler flows such as TVM, XLA, Glow, and custom runtime engines. ️ Media & Sensor Processing Pipelines Architect pipelines involving camera input , ISP tuning , video codecs , audio preprocessors , or sensor fusion stacks . Integrate media frameworks such as V4L2 , GStreamer , and OpenCV into real-time embedded systems. Optimize for frame latency, buffering, memory reuse, and bandwidth constraints in edge deployments. ️ Embedded Firmware & Platform Leadership Lead board bring-up, firmware development (RTOS/Linux), peripheral interface integration, and low-power system design. Work with engineers across embedded, AI/ML, and cloud to build robust, secure, and production-ready systems. Review schematics and assist with hardware–software trade-offs, especially around compute, thermal, and memory design. Required Qualifications ‍ Education: BE/B.Tech/M.Tech in Electronics, Electrical, Computer Engineering, Embedded Systems, or related fields. Experience: Minimum 5+ years of experience in embedded systems design. Minimum 3 years of hands-on experience with AI accelerators and ML model deployment at the edge. Technical Skills Required Embedded System Design Strong C/C++, embedded Linux, and RTOS-based development experience. Experience with SoCs and MCUs such as STM32, ESP32, NXP, RK3566/3588, TI Sitara, etc. Cross-architecture familiarity: ARM Cortex-A/M, RISC-V, DSP cores. ML & Accelerator Toolchains Proficiency with ML compilers and deployment toolchains: ONNX, TFLite, HailoRT, EdgeTPU compiler, TVM, XLA . Experience with quantization , model pruning , compiler graphs , and hardware-aware profiling . Media & Peripherals Integration experience with camera modules , audio codecs , IMUs , and other digital/analog sensors . Experience with V4L2 , GStreamer , OpenCV , MIPI CSI , and ISP tuning is highly desirable. System Optimization Deep understanding of compute budgeting , thermal constraints , memory management , DMA , and low-latency pipelines . Familiarity with debugging tools: JTAG , SWD , logic analyzers , oscilloscopes , perf counters , and profiling tools. Preferred (Bonus) Skills Experience with Secure Boot , TPM , Encrypted Model Execution , or Post-Quantum Cryptography (PQC) . Familiarity with safety standards like IEC 61508 , ISO 26262 , UL 60730 . Contributions to open-source ML frameworks or embedded model inference libraries. Why Join Us? At EURTH TECHTRONICS PVT LTD , you won't just be optimizing firmware — you will architect full-stack intelligent systems that push the boundary of what's possible in embedded AI. Work on production-grade, AI-powered devices for industrial, consumer, defense, and medical applications . Collaborate with a high-performance R&D team that builds edge-first, low-power, secure, and scalable systems . Drive core architecture and set the technology direction for a fast-growing, innovation-focused organization. How to Apply Send your updated resume + GitHub/portfolio links to: jobs@eurthtech.com 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.

Hyderabad, Telangana, India Job Type Full Time About the Role About the Role We are looking for a hands-on and technically proficient Embedded Software Team Lead to drive the development of intelligent edge systems that combine embedded firmware, machine learning inference, and hardware acceleration. This role is perfect for someone who thrives at the intersection of real-time firmware design, AI model deployment, and hardware-software co-optimization. You will lead a team delivering modular, scalable, and efficient firmware pipelines that run quantized ML models on accelerators like Hailo, Coral, Torrent (BlackHole), Kendryte, and other emerging chipsets. Your focus will include model runtime integration, low-latency sensor processing, OTA-ready firmware stacks, and CI/CD pipelines for embedded products at scale Requirements Key Responsibilities Technical Leadership & Planning Own the firmware lifecycle across multiple AI-based embedded product lines. Define system and software architecture in collaboration with hardware, ML, and cloud teams. Lead sprint planning, code reviews, performance debugging, and mentor junior engineers. ️ ML Model Deployment & Runtime Integration Collaborate with ML engineers to port, quantize, and deploy models using TFLite , ONNX , or HailoRT . Build runtime pipelines that connect model inference with real-time sensor data (vision, IMU, acoustic). Optimize memory and compute flows for edge model execution under power/bandwidth constraints. Firmware Development & Validation Build production-grade embedded stacks using RTOS (FreeRTOS/Zephyr) or embedded Linux . Implement secure bootloaders, OTA update mechanisms, and encrypted firmware interfaces. Interface with a variety of peripherals including cameras, IMUs, analog sensors, and radios (BLE/Wi-Fi/LoRa). ️ CI/CD, DevOps & Tooling for Embedded Set up and manage CI/CD pipelines for firmware builds, static analysis, and validation. Integrate Docker-based toolchains, hardware-in-loop (HIL) testing setups, and simulators/emulators. Ensure codebase quality, maintainability, and test coverage across the embedded stack. Required Qualifications ‍ Education: BE/B.Tech/M.Tech in Embedded Systems, Electronics, Computer Engineering, or related fields. Experience: Minimum 4+ years of embedded systems experience. Minimum 2 years in a technical lead or architect role. Hands-on experience in ML model runtime optimization and embedded system integration. Technical Skills Required Embedded Development & Tools Expert-level C/C++ , hands-on with RTOS and Yocto-based Linux . Proficient with toolchains like GCC/Clang, OpenOCD, JTAG/SWD, Logic Analyzers. Familiarity with OTA , bootloaders , and memory management (heap/stack analysis, linker scripts). ML Model Integration Proficiency in TFLite , ONNX Runtime , HailoRT , or EdgeTPU runtimes . Experience with model conversion, quantization (INT8, FP16), runtime optimization. Ability to read/modify model graphs and connect to inference APIs. Connectivity & Peripherals Working knowledge of BLE, Wi-Fi, LoRa, RS485 , USB, and CAN protocols. Integration of camera modules , MIPI CSI , IMUs , and custom analog sensors . ️ DevOps for Embedded Hands-on with GitLab/GitHub CI, Docker, and containerized embedded builds. Build system expertise: CMake , Make , Bazel , or Yocto preferred. Experience in automated firmware testing (HIL, unit, integration). Preferred (Bonus) Skills Familiarity with machine vision pipelines , ISP tuning , or video/audio codec integration . Prior work on battery-operated devices , energy-aware scheduling , or deep sleep optimization . Contributions to embedded ML open-source projects or model deployment tools. Why Join Us? At EURTH TECHTRONICS PVT LTD , we go beyond firmware—we’re designing and deploying embedded intelligence on every device, from industrial gateways to smart consumer wearables. Build and lead teams working on cutting-edge real-time firmware + ML integration . Work on full-stack embedded ML systems using the latest AI accelerators and embedded chipsets . Drive product-ready, scalable software platforms that power IoT, defense, medical , and consumer electronics . How to Apply Send your updated resume + GitHub/portfolio links to: jobs@eurthtech.com 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.

Hyderabad, Telangana, India Job Type Full Time 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: jobs@eurthtech.com 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.

Company Description Maharshi Industries Pvt. Ltd. is a leading authority in Robotics, Special Purpose Machinery (SPM), Embedded Systems, Artificial Intelligence, Virtual reality, and Engineering Design. Their advanced Robotics, AI, and VR solutions are tailored for Defense, Oil & Gas, Railways, Nuclear, and Public Safety sectors, aiming to boost operational efficiency, safety, and resilience. Role Description This is a full-time on-site role for an Artificial Intelligence-Computer Vision Engineer at Maharshi Industries Pvt. Ltd. located in Ahmedabad. The engineer will be responsible for tasks such as pattern recognition, neural networks, software development, and natural language processing as part of their day-to-day responsibilities. We are looking for a Computer Vision-focused AI/ML Engineer who can build robust, real-time models using image/video data. You will work on critical safety, defense, and industrial inspection projects, including: Human detection & identification Behavior recognition (sleeping, loitering, missing person, PPE compliance) Quality Control (QC) anomaly detection – cracks, surface defects, packaging issues Bird detection for aviation safety (runway & airspace) HSSE Compliance Monitoring for Oil & Gas, Railways, and Industrial setups Your work will directly contribute to saving lives, protecting critical infrastructure, and supporting national security missions. Key Responsibilities Develop, train, and deploy deep learning models for object detection, classification, and anomaly detection using CV data Handle datasets including thermal, IR, RGB video , and still images from surveillance or industrial cameras Optimize models for real-time inference on edge devices (Jetson Nano/Xavier, OpenVINO, etc.) Build pipelines for automatic defect and behavior detection in industrial and outdoor environments Collaborate with hardware, VR, and embedded teams for deployment and testing in real-world settings Continuously fine-tune models using on-field data and adversarial conditions. Must-Have Skills Strong experience in AI/ML model development using PyTorch / TensorFlow / Keras Deep understanding of Computer Vision techniques : ▫ Object detection (YOLO, Faster R-CNN, SSD) ▫ Instance segmentation (Mask R-CNN, Detectron2) ▫ Anomaly detection / QC using autoencoders or custom CNNs Hands-on with OpenCV , image preprocessing , and video analytics Familiarity with edge computing platforms (NVIDIA Jetson series, Coral, etc.) Working knowledge of model deployment frameworks (ONNX, TensorRT, Flask APIs) Experience with datasets like COCO, ImageNet , and custom data labeling Skills (Preferred) Bird or animal detection models Human pose estimation or behavior analysis (e.g., OpenPose, MediaPipe, LSTM-based tracking) Background in industrial inspection , aviation , or defense-related AI systems Basic knowledge of Docker , CI/CD , or Linux-based deployments Why Join Us? Work on prestigious projects for Indian Armed Forces, Airports, Oil & Gas PSUs, and DRDO labs Apply your skills in mission-critical real-world AI systems Join a team where innovation meets impact —your code could help save lives and protect national assets

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build what’s next for their businesses. Your Role Job Description Edge AI Data Scientists will be responsible for designing, developing, and validating machine learning models—particularly in the domain of computer vision—for deployment on edge devices. This role involves working with data from cameras, sensors, and embedded platforms to enable real-time intelligence for applications such as object detection, activity recognition, and visual anomaly detection. The position requires close collaboration with embedded systems and AI engineers to ensure models are lightweight, efficient, and hardware-compatible. Candidate Requirements Education Bachelor's or Master’s degree in Data Science, Computer Science, or a related field. Experience 3+ years of experience in data science or machine learning with a strong focus on computer vision. Experience in developing models for edge deployment and real-time inference. Familiarity with video/image datasets and deep learning model training. Skills Proficiency in Python and libraries such as OpenCV, PyTorch, TensorFlow, and FastAI. Experience with model optimization techniques (quantization, pruning, etc.) for edge devices. Hands-on experience with deployment tools like TensorFlow Lite, ONNX, or OpenVINO. Strong understanding of computer vision techniques (e.g., object detection, segmentation, tracking). Familiarity with edge hardware platforms (e.g., NVIDIA Jetson, ARM Cortex, Google Coral). Experience in processing data from camera feeds or embedded image sensors. Strong problem-solving skills and ability to work collaboratively with cross-functional teams. Your Profile Responsibilities Develop and train computer vision models tailored for constrained edge environments. Analyze camera and sensor data to extract insights and build vision-based ML pipelines. Optimize model architecture and performance for real-time inference on edge hardware. Validate and benchmark model performance on various embedded platforms. Collaborate with embedded engineers to integrate models into real-world hardware setups. Stay up-to-date with state-of-the-art computer vision and Edge AI advancements. Document models, experiments, and deployment configurations. What You Will Love About Working Here· We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital andiCa sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.

Responsibilities: Overall 8+ years of experience, out of which in 4+ in AI, ML and Gen AI and related technologies Proven track record of leading and scaling AI/ML teams and initiatives Strong understanding and hands-on experience in AI, ML, Deep Learning, and Generative AI concepts and applications Expertise in ML frameworks such as PyTorch and/or TensorFlow Experience with ONNX runtime, model optimization and hyperparameter tuning Solid Experience of DevOps, SDLC, CI/CD, and MLOps practices - DevOps/MLOps Tech Stack: Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, ELK stack Experience in production-level deployment of AI models at enterprise scale Proficiency in data preprocessing, feature engineering, and large-scale data handling Expertise in image and video processing, object detection, image segmentation, and related CV tasks Proficiency in text analysis, sentiment analysis, language modeling, and other NLP applications Experience with speech recognition, audio classification, and general signal processing techniques Experience with RAG, VectorDB, GraphDB and Knowledge Graphs Extensive experience with major cloud platforms (AWS, Azure, GCP) for AI/ML deployments. Proficiency in using and integrating cloud-based AI services and tools (e.g., AWS SageMaker, Azure ML, Google Cloud AI) Required Skills: Strong leadership and team management skills Excellent verbal and written communication skills Strategic thinking and problem-solving abilities Adaptability and adapting to the rapidly evolving AI/ML landscape Strong collaboration and interpersonal skills Ability to translate market needs into technological solutions Strong understanding of industry dynamics and ability to translate market needs into technological solutions Demonstrated ability to foster a culture of innovation and creative problem-solving

AI Lead – Generative & Agentic AI Systems Experience: 7–10 Years Location: Hyderabad (Hybrid) Employment Type: Full-Time About the Role: We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities: Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise: AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications: 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Types: Full-time, Permanent Pay: ₹2,500,000.00 - ₹3,500,000.00 per year Benefits: Flexible schedule Health insurance Provident Fund Supplemental Pay: Joining bonus Work Location: In person

We are seeking an experienced Generative AI Engineer to design, develop, and optimize AI models for text, image, video, and audio generation. The ideal candidate should have expertise in deep learning, natural language processing (NLP), transformer models (GPT, BERT, LLaMA, etc.), and multimodal AI. This role involves working with large-scale datasets, fine-tuning AI models, and deploying scalable AI solutions. Key Responsibilities: Design, develop, and fine-tune Generative AI models for text, image, video, and audio synthesis. Work with transformer architectures such as GPT, BERT, T5, Stable Diffusion, and CLIP. Implement and optimize LLMs (Large Language Models) using Hugging Face, OpenAI, or custom architectures. Develop AI-powered chatbots, virtual assistants, and content generation tools. Work with diffusion models, GANs (Generative Adversarial Networks), and VAEs (Variational Autoencoders) for creative AI applications. Optimize AI models for performance, inference speed, and cost efficiency in cloud or edge environments. Deploy AI models using TensorFlow, PyTorch, ONNX, and MLflow on AWS, Azure, or GCP. Work with vector databases (FAISS, Pinecone, Weaviate) and embedding-based search techniques. Fine-tune models using RLHF (Reinforcement Learning with Human Feedback) for better alignment. Collaborate with data scientists, ML engineers, and product teams to integrate AI capabilities into applications. Ensure AI model security, bias mitigation, and ethical AI practices. Stay updated with the latest advancements in Generative AI, foundation models, and prompt engineering. Required Skills & Qualifications: 6+ years of experience in AI, machine learning, and deep learning. Strong expertise in Generative AI models and transformer architectures. Proficiency in Python, TensorFlow, PyTorch, and Hugging Face libraries. Experience with NLP, text embeddings, and retrieval-augmented generation (RAG). Knowledge of vector databases, embeddings, and scalable model serving (FastAPI, Triton, Ray Serve). Experience with GPU acceleration (CUDA, TensorRT, ONNX optimization) for AI workloads. Familiarity with cloud-based AI services like AWS Bedrock, Azure OpenAI, or Google Vertex AI. Strong understanding of data preprocessing, annotation, and model evaluation metrics. Experience working with large-scale datasets and distributed training techniques. Strong problem-solving skills and ability to work in Agile/DevOps environments. Preferred Qualifications: Experience with multimodal AI (text-to-image, text-to-video, speech synthesis). Knowledge of RLHF, prompt engineering, and AI-assisted code generation. Certifications in Machine Learning, AI, or Cloud AI services.

We are hiring a contract-based Computer Vision Engineer in Hyderabad, India to lead deep learning model development using PyTorch. The ideal candidate will design and deploy scalable computer vision pipelines focused on image and video analytics. This is a 6-month engagement to support real-time model deployment, optimization, and automation across cloud and edge platforms. Key Responsibilities 1. Deep Learning Model Development • Build and train state-of-the-art CV models using PyTorch for classification, detection (YOLO, Faster R-CNN), and segmentation (UNet, DeepLab) • Optimize data pipelines and preprocessing strategies for high-resolution image and video feeds • Fine-tune pre-trained models and manage custom model development based on project needs 2. Model Optimization & Deployment • Optimize models using ONNX, quantization, or TensorRT for cloud and edge deployment • Deploy real-time inference endpoints using containers (Docker/Kubernetes) and cloud services (Azure, AWS, GCP) • Maintain experiment tracking, model versioning, and deployment automation workflows 3. Data Engineering & Integration • Work with data engineers to build scalable data pipelines for ingestion and preprocessing • Integrate CV models into production systems and IoT environments (e.g., Jetson, Azure IoT) 4. Governance & Performance • Ensure AI workflows are secure, auditable, and production-ready • Apply model compression and tuning for performance at scale 5. Cross-functional Collaboration • Collaborate with DevOps, product teams, and ML engineers for seamless delivery • Document architectures and ensure knowledge transfer at project milestones Required Qualifications • Bachelor’s or Master’s in Computer Science, AI/ML, or a related technical field • 5+ years of experience in AI/ML with at least 2 years in deploying PyTorch-based CV models • Expertise in PyTorch, OpenCV, Python, Git, and deep learning model deployment • Familiarity with cloud platforms (Azure preferred), Docker/Kubernetes • Hands-on experience with model lifecycle tools (MLflow, W&B, DVC, etc.) Preferred Qualifications • Experience with edge AI platforms (Jetson, Coral, Azure Percept) • Knowledge of ONNX, TensorRT, or other optimization tools • Exposure to enterprise-grade security practices and MLOps workflows Contract Details • Duration: 6 months • Location: Hyderabad (Hybrid preferred; remote may be considered for exceptional candidates) • Compensation: Competitive, based on experience and expertise How to Apply Send your resume, portfolio (if available), and GitHub/LinkedIn profiles to: Info@primeverse.in Subject: Computer Vision Engineer – Hyderabad

You will join Logitechs Hardware Audio DSP and ML Product team to develop real-time Audio ML solutions that redefine customer audio experiences. The role requires a strong foundation in Audio Machine Learning and Digital Signal Processing. Responsibilities: Lead and Develop Innovative audio signal processing solutions for Multi-Channel Speech enhancement, Acoustic echo cancellation, Audio event classification, Spatial Audio using deep learning techniques. Lead and work on the end-to-end ML workflow from Data preparation, Model architecture design, Training, Deployment and evaluation of Audio ML targeting resource-constrained platforms such as Tensilica DSP, ARM, RISCV cores.and NPUs. Optimize and enhance algorithm performance under real-world conditions by proposing innovative solutions to complex challenges. Collaborate with cross-functional product teams to deliver seamless audio experiences for customers. Key Qualifications: 10+ years of experience in Audio signal processing and Machine learning with a proven track record of successfully delivering robust Audio ML solutions on schedule. Strong programming skills and hands-on experience using the following languages and ML frameworks: Python, C, TFL/LiteRT, Tensorflow, ONNX, PyTorch Strong knowledge of Audio Quality and Intelligibility assessment objective and subjective metrics. Adept at identifying audio artifacts and showcasing excellent listening skills. Strong leadership skills and experience working collaboratively with cross-functional teams. Strong problem-solving and communication skills Additional Skills: Deep understanding of state-of-the-art quantization techniques (e.g., training-aware quantization or mixed precision) to improve runtime efficiency. Identify and resolve performance bottlenecks in ML inference on embedded systems. Experience working on consumer audio products in the full hardware product lifecycle, including mass production. Passionate about Audio ML, being hands on and seeing your work come to life. Staying on top of emerging trends.

Key Responsibilities Design, develop, and deploy deep learning models for image classification, object detection, segmentation, pose estimation, OCR, and related tasks. Work with large-scale datasets (images, videos, annotations), including data cleaning, augmentation, and preprocessing pipelines. Evaluate and fine-tune models using metrics like IoU, mAP, F1 score, and accuracy. Conduct research and experimentation with state-of-the-art architectures such as CNNs, Transformers (ViT, DETR), GANs, and self-supervised learning. Collaborate with cross-functional teams to integrate models into production pipelines (cloud/on-prem). Stay current with the latest advancements in computer vision and contribute to the company’s innovation roadmap. Develop tools for model explainability and performance monitoring in production environments. Required Qualifications B.Tech, Master’s or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. 3+ years of experience in developing and deploying deep learning models for computer vision tasks. Strong proficiency in Python and deep learning frameworks like PyTorch and TensorFlow. Hands-on experience with libraries such as OpenCV, Albumentations, MMDetection, Detectron2, or YOLOv5/8. Experience training and optimizing models on GPU clusters using distributed training (e.g., PyTorch Lightning, DDP). Familiarity with model deployment (ONNX, TensorRT, TorchScript) and serving (FastAPI, Flask, Triton Inference Server). Experience with annotation tools (e.g., CVAT, Labelbox) and data versioning tools (e.g., DVC, Weights & Biases). Strong understanding of computer vision metrics and evaluation protocols. Strong skillset in mathematical algorithmics and explainability of deep learning models and frameworks. Preferred Skills Knowledge of 3D vision, SLAM, multi-view geometry and YOLO. Experience working with video datasets and spatio-temporal models. Background in self-supervised or semi-supervised learning. Familiarity with MLOps pipelines and tools like MLflow, Kubeflow, or SageMaker Experience in a domain-specific application like medical imaging, aerial imagery, or autonomous vehicles. Why Join Us Work on impactful AI products at the cutting edge of computer vision. Collaborate with a world-class team of researchers and engineers. Access to state-of-the-art GPU infrastructure and training platforms. Flexible work environment with competitive compensation and benefits.

Dear Candidate, We are hiring a Computer Vision Engineer to develop AI-driven solutions for image recognition, object detection, and video analysis. The role requires expertise in deep learning, computer vision algorithms, and real-time processing techniques. Key Responsibilities: Develop and optimize computer vision models using OpenCV, TensorFlow, and PyTorch. Implement object detection, segmentation, and facial recognition algorithms. Process and analyze large-scale image and video datasets. Optimize deep learning models for real-time inference on edge devices. Collaborate with AI and software teams to integrate vision solutions into applications. Required Skills & Qualifications: Computer Vision Frameworks: OpenCV, DLIB, MediaPipe Deep Learning: TensorFlow, PyTorch, Keras Algorithms: CNNs, YOLO, Faster R-CNN, Mask R-CNN Programming: Python, C++, CUDA Edge AI: TensorRT, OpenVINO, NVIDIA Jetson Experience with autonomous systems, OCR, and SLAM is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies