28 Openvino Jobs

About BeGig BeGig is the leading tech freelancing marketplace. We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent. By joining BeGig, youre not just taking on one roleyoure signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise. Your Opportunit yJoin our network as an Edge AI Develope r and bring AI capabilities directly to edge deviceswhere speed, privacy, and offline access matter most. Youll develop, deploy, and optimize machine learning models to run on low-power, low-latency hardware in real-world environments like IoT, robotics, automotive, and smart devices . This fully remote role is available on an hourly or project-based basi s.Role Overvi ewAs an Edge AI Developer, you wil l:Build AI for the Ed ge: Develop and deploy optimized AI models that run directly on embedded or edge device s.Model Optimizati on: Use techniques like quantization, pruning, and compression to reduce model size and inference latenc y.Hardware Integrati on: Work with edge hardware platforms such as NVIDIA Jetson, Raspberry Pi, Coral TPU, and ARM-based board s.Deploy Offline Mode ls: Package and deploy models for inference without requiring constant cloud connectivit y.Performance Tuni ng: Ensure models are fast, accurate, and resource-efficient under real-time constraint s.Toolchain Usa ge: Use platforms like TensorFlow Lite, ONNX, OpenVINO, or PyTorch Mobile for deployment and optimizatio n. Technical Requirements & Ski llsExperie nce: Minimum 2+ years in machine learning, embedded systems, or AI application developme nt.Model Optimizat ion: Experience with tools like TensorRT, TFLite, or ONNX Runtime for edge model optimizati on.Programm ing: Proficiency in Python and C/C++ for model integration, device communication, and real-time processi ng.Hardware Platfo rms: Familiarity with deploying AI models on Jetson Nano, Raspberry Pi, Intel Neural Compute Stick, e tc.Deployment & Test ing: Ability to build testing frameworks to simulate edge scenarios and monitor performan ce.Real-Time Considerati ons: Understanding of latency, thermal constraints, power management, and memory limitatio ns. What Were Looking ForA developer passionate about running AI outside the cloudon devices where speed, efficiency, and privacy are criti cal.A freelancer who can navigate hardware constraints and deliver smart, optimized ML models in product ion.A systems thinker who bridges the gap between machine learning research and embedded engineer ing. Why Joi n UsImmediate I mpact: Help startups deploy AI models into real-world environmentsfrom warehouses to smart h omes.Remote & Fle xible: Work from anywhere and structure your engagement on your own termshourly or project-b ased.Future Opportun ities: Be continuously matched with projects in IoT, robotics, and real-time edg e AI.Growth & Recogn ition: Be part of a trusted network that values cutting-edge technical expertise and applied AI deli very. Show more Show less

JOB TITLE: AI ASSOCIATE OPTIMIZATION Location: Bengaluru | Experience: 1-3 Years ABOUT NEWCOLD NewCold is a service provider in cold chain logistics with a focus on development and operation of large, highly automated cold stores. NewCold strives to be crucial in the cold chain of leading food companies, by offering advanced logistic services worldwide. NewCold is one of the fastest growing companies (over 2,000 employees) in the cold chain logistics and they are expanding teams to support this growth. They use the latest technology that empowers people, to handle food responsibly and guarantee food safety in a sustainable way. They challenge the industry, believe in long-term partnerships, and deliver solid investment opportunities that enable next generation logistic solutions. NewCold has leading market in-house expertise in designing, engineering, developing and operating state-of-the-art automated cold stores: a result of successful development and operation of over 15 automated warehouses across three continents. With the prospect of many new construction projects around the world in the very near future, this vacancy offers an interesting opportunity to join an internationally growing and ambitious organization. POSITION SUMMARY NewCold is seeking an AI Associate Optimization to enhance the performance and efficiency of our AI-powered solutions within our highly automated cold chain logistics network. This role focuses on optimizing machine learning models deployed in warehouse operations, ensuring low latency, high throughput, and accurate predictions for improved decision-making. You will be instrumental in bridging the gap between data science and real-world deployment, contributing to the continuous improvement of our automated systems. This position requires a strong understanding of model serving, containerization, and edge AI technologies. YOUR ROLE As an AI Associate Optimization, you will play a critical role in ensuring the reliability, scalability, and performance of AI models powering NewColds automated warehouse processes. You will be responsible for optimizing models for deployment across diverse infrastructure, including cloud and edge environments, directly impacting operational efficiency, cost reduction, and the overall effectiveness of our logistics solutions. Your work will contribute to maintaining NewColds competitive edge through cutting-edge AI implementation. KEY RESPONSIBILITIES Implement model optimization techniques such as quantization and knowledge distillation to reduce model size and improve inference speed for deployment on edge devices and cloud infrastructure. Develop and maintain CI/CD pipelines for automated model deployment and updates, ensuring seamless integration with existing systems. Benchmark and profile model performance (latency, throughput, memory usage) to identify bottlenecks and areas for improvement. Deploy and manage machine learning models using model serving frameworks like TensorFlow Serving, TorchServe, ONNX Runtime, or Triton Inference Server. Containerize AI models and applications using Docker and Podman for consistent and reproducible deployments. Collaborate with data scientists and software engineers to troubleshoot model performance issues and implement solutions. Monitor model performance in production and proactively address any degradation in accuracy or efficiency. Develop and maintain APIs/SDKs (REST, gRPC, FastAPI) for accessing and integrating AI models into various applications. Work with edge devices (NVIDIA Jetson, Coral TPU, ARM-based boards) and edge frameworks (TensorRT, OpenVINO, TFLite, TVM) to optimize models for low-power, real-time inference. WHAT WE ARE LOOKING FOR Bachelors or masters degree in computer science, Artificial Intelligence, Machine Learning or a related field 1-3 years of experience in a role focused on machine learning model optimization and deployment. Proficiency in Python and C++ programming languages. Hands-on experience with model serving frameworks (TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server). Experience with containerization technologies (Docker, Podman) and orchestration tools (Kubernetes, K3s, Edge orchestrators). Knowledge of model optimization techniques such as quantization and knowledge distillation. Familiarity with benchmarking and profiling tools for evaluating model performance. Strong analytical and problem-solving skills with a data-driven approach. Experience with CI/CD pipelines for ML deployment is highly desirable. Knowledge of edge devices (NVIDIAJetson, Coral TPU, ARM-based boards) and edge AI frameworks (TensorRT, OpenVINO, TFLite, TVM) is a significant plus. WHY JOIN US Opportunity to work on cutting-edge AI applications in a rapidly growing and innovative cold chain logistics company. Exposure to a wide range of AI technologies and challenges within a highly automated warehouse environment. Career growth potential within a dynamic and international organization. Collaborative and supportive team environment with opportunities for learning and development. Contribute to the development of next-generation logistics solutions that are shaping the future of the food supply chain. Show more Show less

Must have skills required : Class Incremental Learning, Computer Vision, Docker/Kubernetes, MLOps, Pytorch, TensorFlow, Vision Transformers, Machine Learning Good to have skills : edge deployment, MLFlow, ONNX, Prometheus/Grafana, Cloud Server (Google / AWS) Radius AI (One of Uplers Clients) is Looking for: ML Ops Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description Were looking for an experienced ML Ops Engineer with a strong foundation in computer vision and a passion for deploying production-grade AI systems. You'll lead the end-to-end lifecycle of our computer vision models from development and training to scalable deployment. The ideal candidate is excited to optimize and scale AI solutions in the real world. Key Responsibilities Drive the end-to-end development and deployment of computer vision models. Build and maintain robust, scalable ML pipelines and deployment workflows. Implement cutting-edge techniques like Vision Transformers (ViT) and class-incremental learning. Collaborate closely with research scientists, data engineers, and software developers. Train Models and optimise them to run on edge GPUs. Automate training, validation, testing, and deployment using CI/CD tools. Monitor model performance in production and optimize for latency, accuracy, and scalability. Ensure reproducibility and versioning of datasets, models, and experiments. Required Qualifications 4+ years of hands-on experience in machine learning and MLOps. Proven experience deploying computer vision models in real-world production environments. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Strong understanding of Vision Transformers (ViT), class-incremental learning, and model version control best practices. Experience with containerization tools like Docker and orchestration using Kubernetes. Familiarity with building and managing ML pipelines using tools such as MLflow, Experience automating CI/CD workflows for machine learning projects. Proficient in Python and scripting for automation. Understanding of data versioning tools and reproducibility standards (e.g., DVC, Weights & Biases). Strong problem-solving skills with the ability to debug and optimize deep learning models in production. Comfortable working with large-scale datasets and real-time data streaming environments. Preferred Qualifications Experience working in startups or fast-paced product teams with a bias for action. Exposure to cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure for ML infrastructure and services. Familiarity with edge deployment strategies and tools like NVIDIA TensorRT or OpenVINO. Understanding of ONNX or other model conversion frameworks. Experience with real-time analytics systems and low-latency model serving. Familiarity with monitoring tools for production ML systems (e.g., Prometheus, Grafana, Sentry). Prior experience in retail or video analytics domains is a plus. Contributions to open-source ML/CV projects or research publications.

As an AI Model Validation Engineer at Leadsoc Technologies in Hyderabad, you will be responsible for validating AI models with a strong background in machine learning fundamentals. Your expertise in deep learning, large language models, and recommender systems within the embedded domain will be essential for this role. To excel in this position, you must possess a solid understanding of validation processes, defects, and the software development life cycle. Proficiency in Ubuntu/Yocto Linux is crucial, along with experience working with open-source frameworks such as PyTorch, TensorFlow, and ONNX-Runtime. Your role will also involve profiling ML workloads and executing validation plans for AI/ML compute stacks like HIP, CUDA, OpenCL, and OpenVINO. Strong python programming skills are a must-have for this position. Ideally, you should have 3-6 years of relevant experience in the field and be available to join with a notice period of less than 15 days. If you are passionate about AI model validation and possess the required skills, we look forward to having you on our team at Leadsoc Technologies. Warm regards, Murali,

We are seeking a highly experienced and skilled Machine Learning Software Engineer with 8-10 years of experience to join our team. The ideal candidate will be a deep learning expert with a strong background in optimizing and deploying machine learning models on specialized hardware, particularly ML accelerators. This role is critical for bridging the gap between theoretical model development and practical, high-performance inference on target platforms. A key focus of this position will be on model quantization and other optimization techniques to maximize efficiency and performance. Key Responsibilities : - Model Porting & Deployment : Port and deploy complex deep learning models from various frameworks (e.g., PyTorch, TensorFlow) to proprietary or commercial ML accelerator hardware platforms (e.g., TPUs, NPUs, GPUs). - Performance Optimization : Analyze and optimize the performance of ML models for target hardware, focusing on latency, throughput, and power consumption. - Quantization : Lead the efforts in model quantization (e.g., INT8, FP16) to reduce model size and accelerate inference while preserving model accuracy. - Profiling & Debugging : Utilize profiling tools to identify performance bottlenecks and debug issues in the ML inference pipeline on the accelerator - Collaboration : Work closely with the ML research, hardware, & software teams to understand model requirements and hardware capabilities, providing feedback to improve both. - Tooling & Automation : Develop and maintain tools and scripts to automate the model porting, quantization, and performance testing workflows - Research & Innovation : Stay current with the latest trends and research in ML hardware, model compression, and optimization techniques. Experience : - 8-10 years of professional experience in machine learning engineering, with a focus on model deployment and optimization. Technical Skills : - Deep expertise in deep learning frameworks such as PyTorch and TensorFlow. - Proven experience in optimizing models for inference on GPUs, NPUs, TPUs, or other specialized accelerators - Extensive hands-on experience with model quantization (e.g., Post-Training Quantization, Quantization-Aware Training). - Strong proficiency in C++ and Python, with experience writing highperformance, low-level code - Experience with GPU programming models like CUDA/cuDNN - Familiarity with ML inference engines and runtimes (e.g., TensorRT, OpenVINO, TensorFlow Lite). - Strong understanding of computer architecture principles, including memory hierarchies, SIMD/vectorization, and cache optimization - Version Control : Proficient with Git and collaborative development workflows - Education : Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field. Preferred Qualifications : - Experience with hardware-aware model design and co-design. - Knowledge of compiler technologies for deep learning. - Contributions to open-source ML optimization projects. - Experience with real-time or embedded systems. - Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps best practices. - Familiarity with CI/CD pipelines and automated testing for ML models - Domain knowledge in areas like computer vision, natural language processing, or speech recognition.

The ideal candidate for the AI/ML position in Bangalore should have a minimum of 6 to 12 years of experience and possess the following must-have skills: - A thorough understanding of AI/ML concepts, Deep Learning, Computer Vision, Natural Language Processing, and Generative AI. - Prior experience in working with DL models, specifically in Computer Vision with frameworks like ResNet, YOLO v3, v4, v5, Efficient Det, etc. - Proficiency in developing Computer Vision applications using DL Frameworks such as TensorFlow, Caffe, Torch, and Toolkits like OpenVINO and TensorRT in both C++ and Python. - Conducting Functional, Performance Tests, and Accuracy Tests on DL Models. - Familiarity with Open Source libraries related to Computer Vision, DL Frameworks, and Toolkits including OpenVINO and TensorRT. - Strong programming skills in C++, with knowledge of the latest standards (C++17) and a background in Object-Oriented Programming. - Experience in performance optimization, developing mathematical routines/kernels with strict performance constraints. Additionally, the following skills are considered good to have: - Exposure to Version Control, Software integration, Continuous Integration, DevOps, Build Tools such as cmake, gcc toolchain, MSVC, etc. - Demonstrated ability to troubleshoot and debug problems in complex systems involving multiple proprietary and open-source components. - Experience in programming on Nvidia GPUs and a solid understanding of the usage of cuDNN and CUDA Libraries. If you possess the required expertise and are enthusiastic about working with cutting-edge technology, we encourage you to apply for this position or reach out to us for more information.,

Principal Engineer (Medtech) About the Role We are seeking a highly experienced Principal Engineer to join our MedTech engineering team.The ideal candidate will bring deep expertise in Cloud, Video technologies, and Edge AI to design and deliver innovative healthcare solutions. This role requires strong technical leadership, hands-on engineering skills, and a proven background in the MedTech domain. Key Responsibilities Lead architecture, design, and implementation of MedTech solutions using Cloud, Video, and Edge AI technologies. Partner with cross-functional teams (Product, Research, and Engineering) to deliver scalable, secure, and compliant healthcare applications. Drive innovation in connected health, video-based diagnostics, and AI at the edge. Ensure adherence to healthcare compliance standards (HIPAA, FDA, MDR, etc.). Mentor and guide engineering teams, fostering technical excellence and best practices. Evaluate new tools, technologies, and frameworks to enhance product capabilities. Required Skills & Experience 12+ years of experience in software engineering with strong exposure to MedTech / Healthcare domain. Proven expertise in Cloud platforms (AWS, Azure, or GCP). Strong knowledge of Video technologies (video streaming, processing, WebRTC, RTP/RTSP). Hands-on experience with Edge AI frameworks (TensorRT, OpenVINO, or similar). Proficiency in microservices, APIs, containerization (Docker, Kubernetes). Strong focus on data security, privacy, and compliance in healthcare applications. Excellent leadership, communication, and problem-solving skills. Preferred Qualifications Experience in IoMT (Internet of Medical Things) or connected devices. Background in medical imaging, diagnostics, or remote patient monitoring. Contributions to patents, publications, or open-source initiatives. Location-Remote, Delhi NCR, Bangalore, Chennai, Pune, Kolkata, Ahmedabad, Mumbai, Hyderabad

As a Staff Software Development Engineer in System Optimization at Netradyne, you will be responsible for implementing and evolving processes to ensure the efficient and high-performance operation of our in-house designed driver monitoring and assistance technology. Your key responsibilities will include crafting and developing tools, frameworks, and reporting mechanisms for system optimization, streamlining software deployment across IoT devices, enhancing data platforms, and optimizing machine learning models deployed on the platform. Additionally, you will be improving driver monitoring and assistance algorithms to boost system efficiency, managing production inquiries, and ensuring overall application stability in production environments. Your role will also involve effectively conveying highly technical results to diverse audiences. To excel in this role, you should hold a B.E/B.Tech or M.E/M.Tech degree with a minimum of 6+ years of experience in software system optimization. You should possess exceptional attention to detail, strong analytical skills, and a creative mindset dedicated to achieving optimal system performance. Proficiency in programming languages such as C/C++, OpenGL, CUDA, and Python is required, along with a solid grasp of basic statistics, probability, and concepts in machine learning (ML) and computer vision (CV). Experience with ML frameworks like Caffe, TensorRT, OpenCL, SNPE, OpenVino, and ONNX, as well as expertise in embedded platforms, make files, build systems, and familiarity with Jenkins, will be valuable assets in this role. Netradyne is actively seeking talented engineers to join our Analytics team, particularly individuals with a strong educational background and past experience in IoT-related companies. If you have prior experience in IoT-related fields and are passionate about optimizing systems and software development, we encourage you to apply and be a part of our innovative team. Join us as a Staff Software Development Engineer in System Optimization and play a pivotal role in enhancing the efficiency and performance of our cutting-edge technology.,

Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power wireless connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the worlds most highly integrated SoCs, Silicon Labs provides device makers the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over 16 countries and is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. Learn more at www.silabs.com. The Role As a Senior QA Engineer in the AI/ML team at Silicon Labs, you will play a pivotal role in defining and upholding quality standards for machine learning and deep learning models deployed on IoT edge devices. Based at our Hyderabad Software Centre of Excellence, you will design automated test frameworks, validate model performance under real-world conditions, and ensure seamless integration of AI technologies into next-generation IoT products. Meet the Team Youll be part of Silicon Labs newly established AI/ML SQA team, working at the forefront of innovation to deliver intelligent IoT solutions. The team collaborates closely with ML developers, DevOps, and product engineers across geographies to support the development, testing, and deployment of ML models and data pipelines. This team is responsible for building the foundation of quality assurance for ML models, enabling cutting-edge IoT products powered by artificial intelligence. Responsibilities : Develop and execute test strategies for machine learning, deep learning, and Tiny LLM models running on IoT edge devices. Validate model accuracy, robustness, and scalability under real-world IoT data conditions. Design automated frameworks to test data pipelines, feature extraction, inference performance, and edge/cloud integration. Ensure seamless integration of ML/DL modules into the IoT platform software stack (firmware, middleware, connectivity, and cloud APIs). Collaborate with ML developers to ensure models meet production-grade quality standards. Work with DevOps engineers to integrate ML model validation into CI/CD workflows. Requirements : Bachelors degree in Electrical Engineering or Computer Science (or equivalent combination of education and experience. 5+ Years of relevant industry experience Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, scikit-learn. Experience in designing and executing automated test frameworks for ML/DL systems. Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI. Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU). Knowledge of MLOps practices, including model versioning and deployment workflows. Understanding of natural language processing and Tiny LLMs is a plus. Benefits & Perks At Silicon Labs, youll be part of a highly skilled team where every engineer makes a meaningful impact. We promote work-life balance and a welcoming, fun environment. Equity Rewards (RSUs) Employee Stock Purchase Plan (ESPP) Insurance plans with outpatient cover National Pension Scheme (NPS) Flexible work policy Childcare support Silicon Labs is an equal opportunity employer and values the diversity of our employees. Employment decisions are made on the basis of qualifications and job-related criteria without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other characteristic protected by applicable law. Show more Show less

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Business Analyst , Data Scientist In this role, w e are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models&mdashensuring they are efficiently trained, deployed, monitored , and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You&rsquoll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow , Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe , Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT , or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Qualifications we seek in you! Minimum Qualifications: Bachelor&rsquos or master&rsquos in computer science , Engineering, or a related field. Sound experience in ML engineering, with significant work in computer vision and model operations. Strong coding skills in Python and familiarity with scripting for automation. Hands-on experience with PyTorch , TensorFlow, OpenCV, and model lifecycle tools like MLflow , DVC, or SageMaker. Solid understanding of containerization and orchestration (Docker, Kubernetes). Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: Experience with real-time video analytics or image-based inference systems. Knowledge of MLOps best practices (model registries, lineage, versioning). Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT , DeepStream ). Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD ). Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Project Role : Software Development Lead Project Role Description : Develop and configure software systems either end-to-end or for a specific stage of product lifecycle. Apply knowledge of technologies, applications, methodologies, processes and tools to support a client, project or entity. Must have skills : Automotive ECU Software Good to have skills : Jetbeans Minimum 7.5 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: We are seeking a highly skilled and experienced C++ Engineer with experience in Computer Vision and Image processing to develop and optimize image processing and computer vision applications across desktop and embedded platforms. The ideal candidate will bring hands-on expertise in C++, OpenCV, and AI/ML frameworks, with a solid understanding of real-time systems and multi-threaded applications. You will be involved in the full software development lifecyclefrom requirements gathering to deploymentwhile collaborating with cross-functional teams on innovative solutions for real-world problems such as vehicle recognition, tread depth estimation, and sensor fusion. Roles & Responsibilities: - Design, develop, and maintain robust computer vision and image processing solutions for practical, field-deployed systems. - Translate project requirements into technical specifications and implement efficient software modules. - Contribute to multi-platform development, including desktop and embedded systems (Linux, Windows, Android). - Optimize performance of algorithms using profiling tools, multi-threading, and hardware acceleration. - Participate in code reviews, design sessions, and mentor junior engineers. - Continuously improve development workflows, coding standards, and integration pipelines. - 69 years of experience in computer vision / image processing. - Strong programming expertise in C++ and Python. - Hands-on experience with OpenCV, OpenGL, Qt/GTK, and multi-threaded programming. - Proficiency in one or more AI/ML frameworks (PyTorch, TensorFlow, or Keras). - Experience with socket communication, real-time systems, and backend databases (SQL-based). - Solid understanding of data structures, algorithms, and system performance tuning. - Familiarity with software development in Linux, Windows, and embedded environments. - Good To have - Experience with embedded platforms (e.g., Jetson, Raspberry Pi, Android-based systems). Knowledge of hardware acceleration frameworks such as OpenVINO or CUDA. Exposure to DevOps tools, CI/CD practices, and containerization (e.g., Docker). Experience in industrial automation, automotive systems, or smart surveillance. Professional & Technical Skills: - Develop and optimize image processing algorithms using C++ and OpenCV for use cases like: Tread depth measurement Vehicle detection and identification Pressure and structural analysis - Work with modern frameworks and libraries such as: OpenVINO, OpenGL, Qt, GTK, Dlib, OpenMP, MPI, Android NDK Deep learning libraries including PyTorch, TensorFlow, and Keras - Use a range of programming languages depending on project needs: C++, Python, C#, Lisp - Develop using IDEs such as Visual Studio, VS Code, Qt Creator, Xcode, and Spyder. - Build and maintain backend systems using MySQL, MS SQL Server, and SQLite. - Implement socket-based communication and multi-threading for real-time data transfer and processing. - Apply strong data structures and algorithmic knowledge to enhance system performance and reliability. - Work with hardware and embedded teams to integrate sensor data and ensure seamless hardware-software interfacing. - Support deployment, testing, and debugging across multiple platforms and hardware configurations. - Keep up with the latest advancements in computer vision, AI/ML, and edge computing technologies. - Document technical architecture, decisions, and module-level workflows. - Engage in client interactions to provide technical insights, feedback, and support for ongoing and upcoming projects. Additional Information: - The candidate should have minimum 7.5 years of experience in C++ Programming Language. - This position is based at our Hyderabad office. - A 15 years full time education is required. Show more Show less

Qualcomm India Private Limited is a leading technology innovator in the Engineering Group, specifically in Systems Engineering. As a Qualcomm Systems Engineer, you will be involved in researching, designing, developing, simulating, and validating systems-level software, hardware, architecture, algorithms, and solutions to drive the development of cutting-edge technology. Collaboration across functional teams is essential to meet and exceed system-level requirements and standards. To qualify for this role, you should possess a Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with at least 8 years of experience in Systems Engineering. Alternatively, a Master's degree with 7+ years of experience or a Ph.D. with 6+ years of experience in the same field is also acceptable. Currently, Qualcomm is seeking a Principal AI/ML Engineer with expertise in model inference, optimization, debugging, and hardware acceleration. The role focuses on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across various hardware platforms. In addition to hands-on engineering tasks, the role also involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques. The ideal candidate will collaborate with researchers, industry experts, and open-source communities to enhance AI performance continuously. The suitable candidate should have a minimum of 20 years of experience in AI/ML development, with a focus on model inference, optimization, debugging, and Python-based AI deployment. A Master's or Ph.D. in Computer Science, Machine Learning, or AI is preferred. Key Responsibilities of this role include Model Optimization & Quantization, AI Hardware Acceleration & Deployment, and AI Research & Innovation. The candidate should have expertise in optimizing deep learning models, familiarity with deep learning frameworks, proficiency in CUDA programming, and experience with various ML inference runtimes. Qualcomm encourages applicants from diverse backgrounds and is an equal opportunity employer. The company is committed to providing reasonable accommodations to individuals with disabilities during the hiring process. It is vital for all employees to adhere to applicable policies and procedures, including those related to confidentiality and security. Qualcomm does not accept unsolicited resumes or applications from staffing and recruiting agencies. For further information about this role, interested individuals may reach out to Qualcomm Careers.,

Job Description We are seeking a highly skilled AI/ML Validation Engineer with a strong foundation in machine learning, deep learning, and system-level validation. The ideal candidate will have hands-on experience with ML frameworks, profiling tools, and AI compute stacks, and will play a key role in validating end-to-end AI pipelines and ensuring software quality across diverse platforms. Responsibilities Design and execute validation plans for AI/ML compute stacks (HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime, TensorFlow, PyTorch). Validate end-to-end AI pipelines including model conversion, inference runtimes, compilers/toolchains, kernel execution, and memory transfer. Profile ML workloads and optimize performance across platforms. Collaborate with global teams to ensure high-quality deliverables. Apply software development lifecycle practices to validation workflows. Document defects, validation results, and improvement recommendations. Primary Skills Strong knowledge of ML fundamentals, deep learning, LLMs, and recommender systems. Proficiency in Python programming. Experience with PyTorch, TensorFlow, ONNX Runtime. Familiarity with Ubuntu/Yocto Linux environments. Expertise in profiling tools and performance analysis. Strong understanding of software QA methodologies. Secondary Skills Experience with compilers/toolchains like TVM, Vitis AI, XDNA, XLA. Exposure to production-grade software validation workflows. Excellent problem-solving and communication skills. Educational Qualification Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Lead Consultant - ML/CV Ops Engineer ! We are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models&mdashensuring they are efficiently trained, deployed, monitored , and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You&rsquoll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Key Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow , Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe , Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT , or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos in Computer Science , Engineering, or a related field. Sound experience in ML engineering, with significant work in computer vision and model operations. Strong coding skills in Python and familiarity with scripting for automation. Hands-on experience with PyTorch , TensorFlow, OpenCV, and model lifecycle tools like MLflow , DVC, or SageMaker. Solid understanding of containerization and orchestration (Docker, Kubernetes). Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: Experience with real-time video analytics or image-based inference systems. Knowledge of MLOps best practices (model registries, lineage, versioning). Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT , DeepStream ). Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD ). Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

The role requires you to design, develop, and maintain complex, high-performance, and scalable MLOps systems that interact with AI models and systems. You will collaborate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to comprehend requirements, define project scope, and ensure alignment with business goals. Your expertise will be crucial in selecting, evaluating, and implementing software technologies, tools, and frameworks within a cloud-native (Azure + AML) environment. Troubleshooting and resolving intricate software issues to ensure optimal performance and reliability when interfacing with AI/ML systems is an essential part of your responsibilities. Additionally, you will contribute to software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery. Your role involves contributing to the development of continuous integration and continuous deployment (CI/CD) pipelines, high-performance data pipelines, storage systems, and data processing solutions. You will drive the integration of GenAI models, such as LLMs and foundation models, into production workflows, including overseeing orchestration and evaluation pipelines. Moreover, you will provide support for edge deployment use cases through model optimization, conversion (e.g., to ONNX, TFLite), and containerization for edge runtimes. Your contribution to creating and maintaining technical documentation, including design specifications, API documentation, data models, data flow diagrams, and user manuals, will be vital for effective communication within the team. **Required Qualifications:** - Bachelor's degree in software engineering/computer science or related discipline - Minimum of 6 years of experience in machine learning operations or software/platform development - Strong familiarity with Azure ML, Azure DevOps, Blob Storage, and containerized model deployments on Azure - Proficiency in programming languages commonly used in AI/ML, such as Python, R, or C++ - Experience with Azure cloud platform, machine learning services, and industry best practices **Preferred Qualifications:** - Experience with machine learning frameworks like TensorFlow, PyTorch, or Keras - Familiarity with version control systems like Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps - Knowledge of containerization technologies such as Docker and Kubernetes, along with infrastructure-as-code tools like Terraform or Azure Resource Manager (ARM) templates - Exposure to Generative AI workflows, including prompt engineering, LLM fine-tuning, or retrieval-augmented generation (RAG) - Understanding of GenAI frameworks like LangChain, LlamaIndex, Hugging Face Transformers, and OpenAI API integration - Experience in deploying optimized models on edge devices using ONNX Runtime, TensorRT, OpenVINO, or TFLite - Hands-on experience with monitoring LLM outputs, feedback loops, or LLMOps best practices - Familiarity with edge inference hardware such as NVIDIA Jetson, Intel Movidius, or ARM Cortex-A/NPU devices This is a permanent position requiring in-person work.,

As a Lead AI ML Developer at Reverence Technologies, you will be leading a team of machine learning and computer vision engineers to deliver high-quality AI/ML solutions for video analytics projects. In this full-time onsite role, located in Noida & Kochi, you will be responsible for collaborating with cross-functional teams to understand business requirements, develop project plans, and ensure the scalability and maintainability of AI/ML solutions. With over 10 years of experience, you will leverage your expertise in developing and deploying machine learning models to guide the team towards successful project outcomes. Your role will involve staying updated with the latest AI/ML research and technologies to evaluate their impact on business operations, in addition to managing team performance, providing mentorship, and fostering a positive team culture. To qualify for this position, you should have a minimum of 6 years of experience in developing and deploying machine learning models, along with at least 3 years of experience in leading machine learning teams. Strong programming skills in C++ and other relevant languages are essential, as well as familiarity with machine learning libraries such as OpenCV, OpenVino, TensorFlow, PyTorch, etc. Experience with cloud platforms like AWS, GCP, or Azure will be advantageous, along with excellent communication and interpersonal skills to collaborate effectively with cross-functional teams.,

computer vision or deep learning roles industrial/safety inspection datasets (e.g., PPE detection, visual defect classification). Familiarity with MLOps tools like MLflow, DVC, or ClearML. ONNX, TensorRT, OpenVINO

You are seeking a highly motivated AI/ML Team Lead to lead a team of machine learning and computer vision engineers for a video analytics project. The ideal candidate should have a strong background in developing and deploying machine learning models, with a proven track record of successfully leading teams in AI/ML projects for video analytics. Your responsibilities will include leading the team to deliver high-quality AI/ML solutions, collaborating with cross-functional teams to identify business requirements, developing and maintaining project plans, ensuring scalability and adherence to best practices, staying updated with the latest AI/ML research, and managing team performance while fostering a positive team culture. The desired candidate should have at least 6 years of experience in developing and deploying machine learning models, along with a minimum of 3 years of experience in leading a team of machine learning engineers. Strong programming skills in C++ and another relevant language are required. Additionally, experience with machine learning libraries and SDKs such as OpenCV, OpenVino, TensorRT, TensorFlow, PyTorch, NVIDIA Deepstream SDK, and familiarity with cloud platforms like AWS, GCP, or Azure are essential. Excellent communication and interpersonal skills are necessary to collaborate effectively with cross-functional teams. If you are passionate about AI/ML, have a successful track record in leading teams for project delivery, and are looking to work in a dynamic and innovative environment, we encourage you to apply for this full-time position in the Software Development department.,

As an AI-ML Architect, you will leverage your 10+ years of experience in developing systems software on Windows or Linux to build, train, and optimize neural network data analytics applications. Your hands-on expertise with Deep Learning frameworks such as Pytorch, TensorFlow, or Caffe will be instrumental in enhancing network performance at kernel level for scalability across hardware. You will play a crucial role in developing, training, and tuning Deep Learning software/models while also exploring techniques like Reinforcement Learning, Transfer Learning, and Federated Learning. Your proficiency in Python programming and C/C++ programming, coupled with solid web service development experience, especially in REST API, will enable you to automate deployment, management, scaling, and networking utilizing Dockers and Kubernetes. Experience with Open Vino, One API DPC++, OpenCL, CUDA programming is preferred. Your familiarity with MLOps, Deep learning infrastructure, microservices architecture, and cloud/distributed infrastructure will be key in designing cutting-edge AI solutions. If you are passionate about AI and possess a strong technical background, this role in Bangalore offers an exciting opportunity to drive innovation in AI-ML architecture and contribute to the development of advanced technologies.,

Capgemini Invent is the digital innovation, consulting, and transformation brand of the Capgemini Group. As an Edge AI Data Scientist, you 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 entails 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. Collaboration with embedded systems and AI engineers is essential to ensure that models are lightweight, efficient, and hardware-compatible. To be successful in this role, you should have a Bachelor's or Master's degree in Data Science, Computer Science, or a related field, along with at least 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 are also required. Proficiency in Python and libraries such as OpenCV, PyTorch, TensorFlow, and FastAI is essential. Additionally, you should have experience with model optimization techniques (quantization, pruning, etc.) for edge devices, deployment tools like TensorFlow Lite, ONNX, or OpenVINO, and a strong understanding of computer vision techniques (e.g., object detection, segmentation, tracking). Familiarity with edge hardware platforms, processing data from camera feeds or embedded image sensors, strong problem-solving skills, and the ability to work collaboratively with cross-functional teams are all important skills for this role. Your responsibilities will include developing and training computer vision models tailored for constrained edge environments, analyzing camera and sensor data to extract insights and build vision-based ML pipelines, optimizing model architecture and performance for real-time inference on edge hardware, validating and benchmarking model performance on various embedded platforms, collaborating with embedded engineers to integrate models into real-world hardware setups, and staying up-to-date with state-of-the-art computer vision and Edge AI advancements. At Capgemini, we value flexible work arrangements to provide support for maintaining a healthy work-life balance. Our focus is on your career growth, offering a variety of career growth programs and diverse professions to support you in exploring a world of opportunities. You will have the opportunity to equip yourself with valuable certifications in the latest technologies such as Generative AI. Capgemini is a global business and technology transformation partner, helping organizations accelerate their transition to a digital and sustainable world while creating tangible impact for enterprises and society. With a team of over 340,000 members in more than 50 countries, Capgemini leverages its 55-year heritage to deliver end-to-end services and solutions utilizing strengths from strategy and design to engineering, with market-leading capabilities in AI, cloud, and data, combined with deep industry expertise and a partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.,

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Lead Consultant - ML/CV Ops Engineer ! We are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models&mdashensuring they are efficiently trained, deployed, monitored , and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You&rsquoll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Key Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow , Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe , Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT , or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos in Computer Science , Engineering, or a related field. Sound experience in ML engineering, with significant work in computer vision and model operations. Strong coding skills in Python and familiarity with scripting for automation. Hands-on experience with PyTorch , TensorFlow, OpenCV, and model lifecycle tools like MLflow , DVC, or SageMaker. Solid understanding of containerization and orchestration (Docker, Kubernetes). Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: Experience with real-time video analytics or image-based inference systems. Knowledge of MLOps best practices (model registries, lineage, versioning). Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT , DeepStream ). Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD ). Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Role & responsibilities : Job Title / Designation: Solution Architect/Project Manager/Associate Director based on experience & expertise Business Unit : Embedded Engineering Services (EES) Industry Experience Range : 8+ years Job Location : Preferably Pune / Ahmedabad / Bangalore Shift : General Shift (Mon-Fri) Job Function, Roles & Responsibilities: Lead strategic initiatives and own the practice for Edge AI/ML, data pipelines, and intelligent embedded systems Define and build the competency roadmap for machine learning, deep learning, model deployment, and real-time inferencing on edge platforms Oversee data creation including data collection, dataset curation, annotation, cleaning, augmentation, and synthetic data generation Champion use cases involving sensor fusion, combining data from multiple sources (vision, IMU, radar, audio, etc.) to create robust, efficient, and context-aware edge intelligence solutions Drive edge analytics and on-device learning across verticals such as Industrial Automation, Medical Devices, Automotive, and Smart Consumer Electronics Collaborate with global customers to gather requirements, architect solutions, track project delivery, and ensure alignment with business objectives Support business development with presales solutioning, proposal writing, and effort estimation Drive internal capability building through mentoring, training, and competency development Preferred candidate profile: ________________________________________ Experience: 8+ years in embedded systems, AI/ML, and data engineering, with a strong focus on edge intelligence and real-time systems. At least 3 years in a technical leadership or strategic role. Prior experience in a product engineering services environment preferred. ________________________________________ Area of Expertise: Proven expertise in deploying ML/DL models on edge devices (NVIDIA Jetson, NXP i.MX, Qualcomm QCS, TI Sitara, etc.) Strong knowledge of data workflows: dataset generation, manual/automated annotation, data cleaning, augmentation, and synthetic data creation Deep understanding of sensor fusion techniques combining inputs from vision, audio, IMU, radar, LIDAR, and other sources to improve model accuracy and efficiency Experience in model optimization using TensorRT, ONNX, OpenVINO, TFLite, and TVM Hands-on with TensorFlow, PyTorch, scikit-learn, and signal/image processing techniques Proficient in designing for real-time inference on resource-constrained platforms Exposure to AI accelerators, NPUs, DSPs, and hybrid SoC environments; must have exposure to NVIDIA SoC & Tools Presales, account engagement, and solutioning experience with North American or European clients ________________________________________ Nice to Have: Cloud-edge integration using AWS Greengrass, Azure IoT Edge, GCP Edge TPU Understanding of AI regulatory/safety standards (ISO, IEC, FDA compliance for AI/ML in regulated industries) ________________________________________ Educational Criteria: BE/ME/B.Tech/M.Tech Electronics, Computer Science, AI/ML, Embedded Systems, or Data Science ________________________________________ Travel: Flexibility to travel globally with sales or delivery teams for customer meetings, workshops, and project deployments as needed. Interested and qualified candidate can directly reach Mr. Anup Sharma at 99099-75421 or anup.s@acldigital.com. (staffing partner can communicate over the email)

Role Overview As a Software AI Engineer in the System Optimization team, you will contribute to developing scalable, efficient AI-powered solutions deployed on edge devices. This role involves working with a multidisciplinary team to enhance software performance, optimize resource usage, and streamline AI model integration into production environments. Responsibilities Contribute to the development of tools and frameworks for performance measurement and system optimization. Assist in profiling and tuning AI models and software components for deployment on edge platforms (CPU/GPU/DSP). Support algorithm integration for driver monitoring and driver assistance systems. Help optimize data pipelines and logging/reporting mechanisms to support real-time analytics. Collaborate with senior engineers to identify bottlenecks and implement efficient code. Support debugging and triaging of issues in production and test environments. Required Skills B.E/B.Tech or M.E/M.Tech in Computer Science, Electronics, Electrical, or related fields. 23 years of experience in software development, preferably in embedded or IoT environments. Good grasp of CS fundamentals including data structures, algorithms, and operating systems. Proficiency in at least one programming language: C/C++, Python. Basic knowledge of system profiling, performance tuning, or resource optimization. Familiarity with ML/CV concepts and frameworks such as OpenCV, TensorFlow, PyTorch, or ONNX is a plus. Exposure to build systems (Make/CMake), version control (Git), and CI/CD tools like Jenkins. Preferred (Good to Have) Familiarity with embedded/edge computing platforms such as NVIDIA Jetson, Qualcomm Snapdragon, etc. Exposure to ML optimization tools like TensorRT, SNPE, or OpenVino. Understanding of containerization (Docker) and orchestration (Kubernetes) environments. Hands-on experience with Linux-based development and debugging.

We are looking for a Principal AI/ML Engineer with expertise in model inference, optimization, debugging, and hardware acceleration . This role will focus on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across diverse hardware platforms. In addition to hands-on engineering, this role involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques . You will explore and implement state-of-the-art AI acceleration methods while collaborating with researchers, industry experts, and open-source communities to push the boundaries of AI performance. This is an exciting opportunity for someone passionate about both applied AI development and AI research , with a strong focus on real-world deployment, model interpretability, and high-performance inference. Education & Experience: 20+ years of experience in AI/ML development, with at least 5 years in model inference, optimization, debugging, and Python-based AI deployment. Masters or Ph.D. in Computer Science, Machine Learning, AI. Leadership & Collaboration: Lead a team of AI engineers in Python-based AI inference development. Collaborate with ML researchers, software engineers, and DevOps teams to deploy optimized AI solutions. Define and enforce best practices for debugging and optimizing AI models. Key Responsibilities: Model Optimization & Quantization: Optimize deep learning models using quantization (INT8, INT4, mixed precision etc), pruning, and knowledge distillation. Implement Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) for deployment. Familiarity with TensorRT, ONNX Runtime, OpenVINO, TVM. AI Hardware Acceleration & Deployment: Optimize AI workloads for Qualcomm Hexagon DSP, GPUs (CUDA, Tensor Cores), TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine. Leverage Python APIs for hardware-specific acceleration, including cuDNN, XLA, MLIR. Benchmark models on AI hardware architectures and debug performance issues. AI Research & Innovation: Conduct state-of-the-art research on AI inference efficiency, model compression, low-bit precision, sparse computing, and algorithmic acceleration. Explore new deep learning architectures (Sparse Transformers, Mixture of Experts, Flash Attention) for better inference performance. Contribute to open-source AI projects and publish findings in top-tier ML conferences (NeurIPS, ICML, CVPR). Collaborate with hardware vendors and AI research teams to optimize deep learning models for next-gen AI accelerators. Details of Expertise: Experience optimizing LLMs, LVMs, LMMs for inference. Experience with deep learning frameworks: TensorFlow, PyTorch, JAX, ONNX. Advanced skills in model quantization, pruning, and compression. Proficiency in CUDA programming and Python GPU acceleration using cuPy, Numba, and TensorRT. Hands-on experience with ML inference runtimes (TensorRT, TVM, ONNX Runtime, OpenVINO). Experience working with RunTimes Delegates (TFLite, ONNX, Qualcomm). Strong expertise in Python programming, writing optimized and scalable AI code. Experience with debugging AI models, including examining computation graphs using Netron Viewer, TensorBoard, and ONNX Runtime Debugger. Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, cProfile, Nsight Systems, perf, Py-Spy). Expertise in cloud-based AI inference (AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi). Knowledge of hardware-aware optimizations (oneDNN, XLA, cuDNN, ROCm, MLIR, SparseML). Contributions to open-source community. Publications in International forums conferences journals.

General Summary: 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 Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. Principal Engineer Machine Learning We are looking for a Principal AI/ML Engineer with expertise in model inference , optimization , debugging , and hardware acceleration . This role will focus on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across diverse hardware platforms. In addition to hands-on engineering, this role involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques . You will explore and implement state-of-the-art AI acceleration methods while collaborating with researchers, industry experts, and open-source communities to push the boundaries of AI performance. This is an exciting opportunity for someone passionate about both applied AI development and AI research , with a strong focus on real-world deployment, model interpretability, and high-performance inference . Education & Experience: 20+ years of experience in AI/ML development, with at least 5 years in model inference, optimization, debugging, and Python-based AI deployment. Masters or Ph.D. in Computer Science, Machine Learning, AI Leadership & Collaboration Lead a team of AI engineers in Python-based AI inference development . Collaborate with ML researchers, software engineers, and DevOps teams to deploy optimized AI solutions. Define and enforce best practices for debugging and optimizing AI models Key Responsibilities Model Optimization & Quantization Optimize deep learning models using quantization (INT8, INT4, mixed precision etc), pruning, and knowledge distillation . Implement Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) for deployment. Familiarity with TensorRT, ONNX Runtime, OpenVINO, TVM AI Hardware Acceleration & Deployment Optimize AI workloads for Qualcomm Hexagon DSP, GPUs (CUDA, Tensor Cores), TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine . Leverage Python APIs for hardware-specific acceleration , including cuDNN, XLA, MLIR . Benchmark models on AI hardware architectures and debug performance issues AI Research & Innovation Conduct state-of-the-art research on AI inference efficiency, model compression, low-bit precision, sparse computing, and algorithmic acceleration . Explore new deep learning architectures (Sparse Transformers, Mixture of Experts, Flash Attention) for better inference performance . Contribute to open-source AI projects and publish findings in top-tier ML conferences (NeurIPS, ICML, CVPR). Collaborate with hardware vendors and AI research teams to optimize deep learning models for next-gen AI accelerators. Details of Expertise: Experience optimizing LLMs, LVMs, LMMs for inference Experience with deep learning frameworks : TensorFlow, PyTorch, JAX, ONNX. Advanced skills in model quantization, pruning, and compression . Proficiency in CUDA programming and Python GPU acceleration using cuPy, Numba, and TensorRT . Hands-on experience with ML inference runtimes (TensorRT, TVM, ONNX Runtime, OpenVINO) Experience working with RunTimes Delegates (TFLite, ONNX, Qualcomm) Strong expertise in Python programming , writing optimized and scalable AI code. Experience with debugging AI models , including examining computation graphs using Netron Viewer, TensorBoard, and ONNX Runtime Debugger . Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, cProfile, Nsight Systems, perf, Py-Spy) . Expertise in cloud-based AI inference (AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi). Knowledge of hardware-aware optimizations (oneDNN, XLA, cuDNN, ROCm, MLIR, SparseML). Contributions to open-source community Publications in International forums conferences journals