12 Openvino Jobs

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

AI/ML Architect Experience 10+ years in total, 8+ years in AI/ML development 3+ years in AI/ML architecture Education Bachelors/Masters in CS, AI/ML, Engineering, or similar Title: AI/ML Architect Location: Onsite Bangalore Experience: 10+ years Position Summary: We are seeking an experienced AI/ML Architect to lead the design and deployment of scalable AI solutions. This role requires a strong blend of technical depth, systems thinking, and leadership in machine learning , computer vision , and real-time analytics . You will drive the architecture for edge, on-prem, and cloud-based AI systems, integrating 3rd party data sources, sensor and vision data to enable predictive, prescriptive, and autonomous operations across industrial environments. Key Responsibilities: Architecture & Strategy Define the end-to-end architecture for AI/ML systems including time series forecasting , computer vision , and real-time classification . Design scalable ML pipelines (training, validation, deployment, retraining) using MLOps best practices. Architect hybrid deployment models supporting both cloud and edge inference for low-latency processing. Model Integration Guide the integration of ML models into the IIoT platform for real-time insights, alerting, and decision support. Support model fusion strategies combining disparate data sources, sensor streams with visual data (e.g., object detection + telemetry + 3rd party data ingestion). MLOps & Engineering Define and implement ML lifecycle tooling, including version control, CI/CD, experiment tracking, and drift detection. Ensure compliance, security, and auditability of deployed ML models. Collaboration & Leadership Collaborate with Data Scientists, ML Engineers, DevOps, Platform, and Product teams to align AI efforts with business goals. Mentor engineering and data teams in AI system design, optimization, and deployment strategies. Stay ahead of AI research and industrial best practices; evaluate and recommend emerging technologies (e.g., LLMs, vision transformers, foundation models). Must-Have Qualifications: Bachelors or Master’s degree in Computer Science, AI/ML, Engineering, or a related technical field. 8+ years of experience in AI/ML development, with 3+ years in architecting AI solutions at scale. Deep understanding of ML frameworks (TensorFlow, PyTorch), time series modeling, and computer vision. Proven experience with object detection, facial recognition, intrusion detection , and anomaly detection in video or sensor environments. Experience in MLOps (MLflow, TFX, Kubeflow, SageMaker, etc.) and model deployment on Kubernetes/Docker . Proficiency in edge AI (Jetson, Coral TPU, OpenVINO) and cloud platforms (AWS, Azure, GCP). Nice-to-Have Skills: Knowledge of stream processing (Kafka, Spark Streaming, Flink). Familiarity with OT systems and IIoT protocols (MQTT, OPC-UA). Understanding of regulatory and safety compliance in AI/vision for industrial settings. Experience with charts, dashboards, and integrating AI with front-end systems (e.g., alerts, maps, command center UIs). Role Impact: As AI/ML Architect, you will shape the intelligence layer of our IIoT platform — enabling smarter, safer, and more efficient industrial operations through AI. You will bridge research and real-world impact , ensuring our AI stack is scalable, explainable, and production-grade from day one.

ML Engineer Position - ML - Engineer Experience - 7+ yrs Client Name - Honeywell International Ltd Payroll Company - Bramha Tech CTC - As per industry norms Job Location - Pune Notice Period - Immediate/ serving Notice Objectives of this role • Design and develop efficient computer vision applications for security and surveillance domain. • Develop computer vision applications and algorithms for deploying on low power embedded devices. • Collaborate with firmware engineers, front-end engineers, QA Engineers and architects on production systems and applications. • Identify differences in data distribution that could potentially affect model performance in real world applications • Ensure algorithms generate accurate predictions. • Stay up to date with developments in the machine learning industry. • Do Data versioning as well as model versioning of the collected data and developed models. Skills and qualifications • Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms. • Familiarity with deploying deep learning models on low power embedded devices. • Good knowledge of programming with C and C++ is must. • Proven record of working with AI Accelerators, NPU and quantization frameworks like OpenVINO or Neuralmagic. • In-depth knowledge of TF or PyTorch. • Familiarity of ArmNN, Kendryte NNcase, Maix Sipeed or RKNN toolkits. • Good knowledge of version control systems like Git, Azure Repos. • Familiarity with data structures, data modeling, and software architecture. • Impeccable analytical and problem-solving skills Preferred qualifications • Proven experience as a machine learning engineer or similar role • Bachelors degree (or equivalent) in computer science, mathematics, or related field