361 Onnx Jobs - Page 4

Company Description Svitla Systems, Inc. is a global digital solutions company with over 20 years of experience, crafting more than 5,000 transformative solutions for clients worldwide. Our mission is to leverage digital, cloud, data, and intelligent technologies to create sustainable solutions for our clients, enhancing their growth and competitive edge. With a diverse team of over 1,000 technology professionals, Svitla serves a range of clients from innovative startups to Fortune 500 companies across 20+ industries. Svitla operates from 10 delivery centers globally, specializing in areas like cloud migration, data analytics, web and mobile development, and more. We are proud to be a WBENC-certified business and one of the largest, fastest-growing women-owned IT companies in the US. Role Description This is a fully remote, full-time, long-term contractual position with one of our clients who is building the next generation of secure, real-time proctoring solutions for high-stakes exams. We’re looking for a Senior ML/AI Engineer to architect, implement, and maintain Azure-based AI models that power speech-to-text, computer vision, identity verification, and intelligent chat features during exam sessions. Responsibilities - Implement real-time speech-to-text transcription and audio-quality analysis using Azure AI Speech. - Build prohibited-item detection, OCR, and face-analysis pipelines with Azure AI Vision. - Integrate Azure Bot Service for rule-based, intelligent chat support. - Collaborate with our DevOps Engineer on CI/CD and infrastructure-as-code for AI model deployment. - Train, evaluate, and deploy object-detection models (e.g., screen-reflection, background faces, ID checks) using Azure Custom Vision. - Develop and maintain skeletal-tracking models (OpenPose/MediaPipe) for gaze-anomaly detection. - Fine-tune Azure Face API for ID-to-headshot matching at session start and continuous identity validation. - Expose inference results via REST APIs in partnership with backend developers to drive real-time proctor dashboards and post-session reports. - Monitor model performance, manage versioning/retraining workflows, and optimize accuracy for edge-case scenarios. Qualifications - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. - 5+ years of professional ML/AI experience, with at least 2 years working on production-grade Azure Cognitive Services. - Strong Python skills plus 3+ years with TensorFlow or PyTorch. - Hands-on experience (1–2 years) with: - Azure AI Speech (speech-to-text, audio analysis) - Azure AI Vision (object detection, OCR, face analysis) - Azure Custom Vision model training and deployment - Azure Face API fine-tuning and biometric matching - Azure Bot Service integration - Solid understanding of CI/CD practices and tools (Azure DevOps, Docker, Kubernetes) with 2+ years of collaboration on AI model deployments. - 2+ years building and consuming RESTful or gRPC APIs for AI inference. - Proven track record of monitoring and optimizing model performance in production. Good to haves - 1+ year with skeletal-tracking frameworks (OpenPose, MediaPipe). - Familiarity with Azure ML Studio, ML pipelines, or MLflow for model versioning and retraining. - Experience with edge-deployment frameworks (TensorFlow Lite, ONNX Runtime). - Background in security and compliance for biometric data (GDPR, PCI-DSS). - Azure AI Engineer Associate or Azure Data Scientist Associate certification. Additional Information -The role is a Fully Remote, Full-Time, Long-Term, Contractual position -The hiring process includes an initial screening by the recruitment team, an HR motivation interview, an internal tech screening, a client technical interview and finally the client management interview -The salary range for this position is 50-70 LPA (INR) -The position needs to be filled on priority, only candidates who have an official notice period (or remaining time on their notice period) of <=30 days will be screened

Pandita AI is a rapidly growing Applied AI startup headquartered in Palo Alto, California , with an Applied AI division based in Mysore, India . We specialize in building domain-specific LLMs , multimodal generative systems , and agentic workflows for real-world problems across scientific computing, document intelligence, and industrial automation. We are looking for a Generative AI Applied Scientist to join our core research team in Mysore. This is a high-impact, high-ownership role for those who thrive at the intersection of deep research , problem discovery , and real-world deployment . Key Responsibilities Proactively identify high-value problem areas where generative AI can deliver measurable impact. Translate ambiguous or emerging needs into well-defined ML tasks and deliver production-grade solutions . Design and develop custom generative models (e.g., Transformers, LLMs, Diffusion Models, VAEs). Own the end-to-end lifecycle of model development — from prototyping to cloud/API deployment . Good communication skills that involve being able to talk to customers, identify problem statements, and communicate impactful results. Collaborate across research, product, and engineering teams to embed generative AI into vertical solutions. Required Qualifications PhD or Masters with Thesis and 5+ years in Computer Science, Machine Learning, AI, or a closely related field. Strong research track record with publications in top-tier conferences (e.g., IEEE TPAMI, CVPR, ICML, ICLR, NeurIPS, ACL ). Expertise in deep generative models , representation learning , and probabilistic methods . Experience in building models that solve real-world problems and can be scaled into production systems . Fluency in Python and modern ML stacks (e.g., PyTorch, JAX, Hugging Face). Willingness to work onsite in Mysore and collaborate across time zones with the US-based HQ. Involves travel about 25-50% to client locations. Preferred Qualifications Experience in LLM fine-tuning , multimodal systems , or diffusion-based generation . Familiarity with retrieval-augmented generation , causal inference , or workflow agents . Experience deploying models via Docker, ONNX, or cloud-native APIs (AWS/GCP). A track record of discovering novel application areas and developing first-of-their-kind solutions. What We Offer A fast-paced startup environment backed by cutting-edge research and global customers. ESOPs/Equity and competitive compensation. Access to high-performance compute (A100s, H100s), internal datasets, and modern MLOps tooling. Clear runway for career growth , technical leadership , and IP ownership . A collaborative and ambitious team working on some of the most important problems in applied AI — from Mysore and Palo Alto .

What You’ll Work On 1. Deep Learning & Computer Vision Train models for image classification: binary/multi-class using CNNs, EfficientNet, or custom backbones. Implement object detection using YOLOv5, Faster R-CNN, SSD; tune NMS and anchor boxes for medical contexts. Work with semantic segmentation models (UNet, DeepLabV3+) for region-level diagnostics (e.g., cell, lesion, or nucleus boundaries). Apply instance segmentation (e.g., Mask R-CNN) for microscopy image cell separation. Use super-resolution and denoising networks (SRCNN, Real-ESRGAN) to enhance low-quality inputs. Develop temporal comparison pipelines for changes across image sequences (e.g., disease progression). Leverage data augmentation libraries (Albumentations, imgaug) for low-data domains. 2. Vision-Language Models (VLMs) Fine-tune CLIP, BLIP, LLaVA, GPT-4V to generate explanations, labels, or descriptions from images. Build image captioning models (Show-Attend-Tell, Transformer-based) using paired datasets. Train or use VQA pipelines for image-question-answer triples. Align text and image embeddings with contrastive loss (InfoNCE), cosine similarity, or projection heads. Design prompt-based pipelines for zero-shot visual understanding. Evaluate using metrics like BLEU, CIDEr, SPICE, Recall@K, etc. 3. Model Training, Evaluation & Interpretation Use PyTorch (core), with support from HuggingFace, torchvision, timm, Lightning. Track model performance with TensorBoard, Weights & Biases, MLflow. Implement cross-validation, early stopping, LR schedulers, warm restarts. Visualize model internals using GradCAM, SHAP, Attention rollout, etc. Evaluate metrics: • Classification: Accuracy, ROC-AUC, F1 • Segmentation: IoU, Dice Coefficient • Detection: mAP • Captioning/VQA: BLEU, METEOR 4. Optimization & Deployment Convert models to ONNX, TorchScript, or TFLite for portable inference. Apply quantization-aware training, post-training quantization, and pruning. Optimize for low-power inference using TensorRT or OpenVINO. Build multi-threaded or asynchronous pipelines for batched inference. 5. Edge & Real-Time Systems Deploy models on Jetson Nano/Xavier, Coral TPU. Handle real-time camera inputs using OpenCV, GStreamer and apply streaming inference. Handle multiple camera/image feeds for simultaneous diagnostics. 6. Regulatory-Ready AI Development Maintain model lineage, performance logs, and validation trails for 21 CFR Part 11 and ISO 13485 readiness. Contribute to validation reports, IQ/OQ/PQ, and reproducibility documentation. Write SOPs and datasheets to support clinical validation of AI components. 7. DevOps, CI/CD & MLOps Use Azure Boards + DevOps Pipelines (YAML) to: Track sprints • Assign tasks • Maintain epics & user stories • Trigger auto-validation pipelines (lint, unit tests, inference validation) on code push • Integrate MLflow or custom logs for model lifecycle tracking. • Use GitHub Actions for cross-platform model validation across environments. 8. Bonus Skills (Preferred but Not Mandatory) Experience in microscopy or pathology data (TIFF, NDPI, DICOM formats). Knowledge of OCR + CV hybrid pipelines for slide/dataset annotation. Experience with streamlit, Gradio, or Flask for AI UX prototyping. Understanding of active learning or semi-supervised learning in low-label settings. Exposure to research publishing, IP filing, or open-source contributions. 9. Required Background 4–6 years in applied deep learning (post academia) Strong foundation in: Python + PyTorch CV workflows (classification, detection, segmentation) Transformer architectures & attention VLMs or multimodal learning Bachelor’s or Master’s degree in CS, AI, EE, Biomedical Engg, or related field 10. How to Apply Send the following to info@sciverse.co.in Subject: Application – AI Research Engineer (4–8 Yrs, CV + VLM) Include: • Your updated CV • GitHub / Portfolio • Short write-up on a model or pipeline you built and why you’re proud of it OR apply directly via LinkedIn — but email applications get faster visibility. Let’s build AI that sees, understands, and impacts lives.

As a Machine Learning Engineer at our company, you will be utilizing your expertise in Computer Vision, Natural Language Processing (NLP), and Backend Development. Your primary responsibilities will include developing ML/DL models for Computer Vision tasks such as classification, object detection, and segmentation, as well as for NLP tasks like text classification, Named Entity Recognition (NER), and summarization. You will also be implementing research papers and creating production-ready prototypes. To excel in this role, you must have a solid understanding of Machine Learning and Deep Learning concepts. Proficiency in tools and libraries like PyTorch, OpenCV, Pillow, TorchVision, and Transformers is essential. You will be optimizing models using techniques such as quantization, pruning, ONNX export, and TorchScript. Moreover, you will be tasked with building and deploying RESTful APIs using FastAPI, Flask, or Django, and containerizing applications using Docker for deployment on cloud or local servers. Your role will also involve writing clean, efficient, and scalable code for backend and ML pipelines. Strong backend skills using FastAPI, Flask, or Django are required, along with experience in utilizing NLP libraries like Hugging Face Transformers, spaCy, and NLTK. Familiarity with Docker, Git, and Linux environments is crucial for this position, as well as experience with model deployment and optimization tools such as ONNX and TorchScript. While not mandatory, it would be advantageous to have knowledge of Generative AI / Large Language Models (LLMs) and experience with MLOps tools like MLflow, DVC, and Airflow. Additionally, familiarity with cloud platforms such as AWS, GCP, or Azure would be a plus. The ideal candidate should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. This is a full-time position with an evening shift schedule from Monday to Friday. The work location is in person.,

You should have at least 2+ years of experience in Machine Learning and Natural Language Processing. Your programming skills should be strong in Python. It is essential to have knowledge of SQL and NoSQL databases. Your expertise should include writing robust code in Python and working with both structured and unstructured data, involving data extraction, integration, and normalization. You should be proficient in ML frameworks/libraries like Tensorflow, Pytorch, ONNX, Scikit Learn, Keras, and Spacy. Additionally, you should possess expert skills in manipulating data frames using Pandas and arrays using NumPy. Experience with big data frameworks such as Spark and Hadoop would be considered a plus. Moreover, familiarity with containerizing applications using docker is also desirable.,

Total yrs of exp: 7+ yrs Balewadi,Pune Location Immediate to 30 Days only Responsibilities - Overall 6+ years of experience, out of which in 5+ in AI, ML and Gen AI and related technologies Proven track record of leading and scaling AI/ML teams and initiatives Strong understanding and hands-on experience in AI, ML, Deep Learning, and Generative AI concepts and applications Expertise in ML frameworks such as PyTorch and/or TensorFlow Experience with ONNX runtime, model optimization and hyperparameter tuning Solid Experience of DevOps, SDLC, CI/CD, and MLOps practices - DevOps/MLOps Tech Stack: Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, ELK stack Experience in production-level deployment of AI models at enterprise scale Proficiency in data preprocessing, feature engineering, and large-scale data handling Expertise in image and video processing, object detection, image segmentation, and related CV tasks Proficiency in text analysis, sentiment analysis, language modeling, and other NLP applications Experience with speech recognition, audio classification, and general signal processing techniques Experience with RAG, VectorDB, GraphDB and Knowledge Graphs Extensive experience with major cloud platforms (AWS, Azure, GCP) for AI/ML deployments. Proficiency in using and integrating cloud-based AI services and tools (e.g., AWS SageMaker, Azure ML, Google Cloud AI) Qualifications - [Education details] Required Skills Strong leadership and team management skills Excellent verbal and written communication skills Strategic thinking and problem-solving abilities Adaptability and adapting to the rapidly evolving AI/ML landscape Strong collaboration and interpersonal skills Ability to translate market needs into technological solutions Strong understanding of industry dynamics and ability to translate market needs into technological solutions Demonstrated ability to foster a culture of innovation and creative problem-solving Preferred Skills Pay range and compensation package - [Pay range or salary or compensation] Equal Opportunity Statement - [Include a statement on commitment to diversity and inclusivity.]

Job Title: Senior CV Engineer Location: Gurugram Experience: 6–10 Years CTC: Up to ₹ 60LPA Overview: We are hiring for our esteemed client, a Series-A funded deep-tech company building a first-of-its-kind app-based operating system for Computer Vision. The team specializes in real-time video/image inference, distributed processing, and high-throughput data handling using advanced technologies and frameworks. Key Responsibilities: Lead design and implementation of complex CV pipelines (object detection, instance segmentation, industrial anomaly detection). Own major modules from concept to deployment ensuring low latency and high reliability. Transition algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer. Collaborate with cross-functional teams to refine technical strategies and roadmaps. Drive long-term data and model strategies (synthetic data generation, validation frameworks). Mentor engineers and maintain high engineering standards. Required Skills & Qualifications: 6–10 years of experience in architecting and deploying CV systems. Expertise in multi-object tracking, object detection, semi/unsupervised learning. Proficiency in Python, PyTorch/TensorFlow, Modern C++, CUDA. Experience with real-time, low-latency model deployment on edge devices. Strong systems-level design thinking across ML lifecycles. Familiarity with MLOps (CI/CD for models, versioning, experiment tracking). Bachelor’s/Master’s degree in CS, EE, or related fields with strong ML and algorithmic foundations. (Preferred) Experience with NVIDIA DeepStream, GStreamer, LLMs/VLMs, open-source contributions.

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.,

You will be responsible for building and maintaining backend logic in PHP (CodeIgniter) and Python (Flask, FastAPI, etc.). Additionally, you will design and implement computer vision workflows using tools such as OpenCV, YOLOv8, MediaPipe, or equivalent tools. Your tasks will involve working with image/video inputs to perform real-time detection of various elements like faces, objects, license plates, hazards, etc. Furthermore, you will integrate with third-party APIs, IoT devices, and edge-based platforms such as Jetson Nano, Raspberry Pi. It will be crucial for you to optimize vision pipelines for enhanced performance, accuracy, and reliability. Your role will also include deploying and enhancing full-stack solutions. To excel in this position, you should hold a Bachelor's degree and possess a minimum of 3 years of hands-on experience with PHP and Python. Demonstrated expertise with OpenCV and YOLO (v5/v8 preferred) is essential. A strong understanding of image processing, video analytics, and real-time detection is required. Proficiency in Linux environments, Git, and REST APIs is expected. Familiarity with edge AI, ONNX, or experience in deploying models on Jetson/Raspberry Pi will be advantageous. Knowledge of object tracking, counting, pose estimation, etc., will also be beneficial for this role.,

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.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: The AI SW team at Qualcomm is focused on advancing state-of-the-art in Artificial Intelligence across various business segments, including Mobile, AR & VR Technology, IoT, and Auto ADAS. The AISW stack leverages Qualcomm chips' extensive heterogeneous computing capabilities, enabling the running of trained neural networks on devices without needing a cloud connection. This allows neural network models trained in various frameworks on Snapdragon platforms to run at blazing speeds while consuming minimal power. As a Senior Lead Engineer, you will see your work directly impact billions of devices worldwide. Key Responsibilities: Design, develop, and maintain high-quality software solutions using Python for running machine learning models on Qualcomm devices. Contribute to the development and optimization of AI models, using popular frameworks like Pytorch. Build tools and infrastructure for onboarding, debugging and analysis of AI models. Participate in code reviews and ensure adherence to best practices and coding standards. Debug accuracy and performance on devices, addressing any challenges that arise. Collaborate with cross-functional teams to define, design, and ship new features. Own end-to-end development and release of features and lead and mentor a sub-team of engineers. Minimum Qualifications: Bachelors degree in engineering, Computer science or a related field and 5+ years of professional experience in software engineering or related work experience OR Masters degree in engineering, Computer science or a related field and 4+ years of experience of Software engineering or related work experience Solid understanding of fundamental computer science concepts, general programming principles and practices. 4+ years of hands-on professional experience in programming with Python (preferred) / Java / C++. Strong problem-solving skills and the ability to work independently and as part of a team. Basic knowledge of AI concepts and techniques Excellent communication skills and the ability to articulate complex technical concepts. Willingness to learn advanced concepts in AI and machine learning and keep updated with latest industry trends Preferred Qualifications: Experience with machine learning frameworks and tools such as PyTorch, ONNX. Familiarity with Large Language Models (LLMs) and Transformers Familiarity working with Linux systems and hardware devices Experience with mobile development frameworks and tools (e.g., Android SDK, Kotlin). Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: More details below Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities: In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Minimum Qualifications Bachelors degree in engineering, Computer Science, or related field and 10+ years of Systems Engineering or related work experience.ORMasters degree in engineering, Computer Science, or related field and 9+ years of Systems Engineering or related work experience. Requirements Strong understanding of Generative AI models- LLM, LVM, LMMs and building blocks (self-attention, cross attention, KV caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU).Hands-on experience in C/C++ programming, Design Patterns and OS concepts.Excellent analytical and debugging skills. Exposure to shell scripts, python scripts, understanding of Linux/Windows systems and automation scripts/environment. Good communication skills, presentation skills and should manage his/her tasks independently. Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Job Area: Engineering Group, Engineering Group > Software Engineering 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 Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience. 4+ years of work experience with Programming Language such as C, C++, Java, Python, etc. 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 Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. In this position you will be responsible for assisting with the software design and development of the Qualcomm Orchestrator SDK and associated tools, specifically targeting various platforms on Snapdragon. Responsibilities Software development of the AI orchestration framework, engine, and tools to develop agentic workflows and execution of the latest Neural Networks on Snapdragon chips. Drive feature development and enhancements needed in the SDK for various platforms. Work closely with the rest of the AI software team and with other internal sub-teams within Qualcomm involved in supporting Orchestrator SDK. Work independently with minimal supervision. Provides supervision/guidance to other team members. Decision-making is significant in nature and affects work beyond immediate work group. Minimum Qualifications Ability to work independently with no supervision Strong communication skills (verbal and written) and an ability to convey complex and detailed information to multiple audiences and high-level stake holders Ability to make decisions and construct plans with minimal, conflicting, and sometimes missing information 12+ years of industry experience 5+ years software development experience on Android/Linux platform and architecture Experience with Android/Linux application development (e.g. integrating applications into the Android/Linux stack ) Software development experience using C/C++ Strong software development skills (e.g. data structure and algorithm design, object oriented or other software design paradigm knowledge, software debugging and testing, etc.) Preferred Qualifications Experience with LLM, LVM, LMM models, ONNX RT and different NN architectures. Linux/Android software development Experience with VectorDB, Faiss, SQLite, MongoDB, NoSQL Software development experience with Python/Java is a plus Ability to collaborate across a globally diverse team and multiple interests Education Requirements RequiredBachelors degree in engineering, Information Systems, Computer Science, or related field. PreferredBachelor's Computer Science, Computer Engineering, or Electrical Engineering Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Qualcomms Audio Systems team is seeking a talented and highly motivated engineer specialized in the implementation of Voice AI and Audio solutions. You will work with a team to prototype, optimize, and productize state-of-the-art ML models, ensuring efficient deployment on snapdragon platforms Responsibilities: - Develop, optimize, and deploy Voice AI and audio ML models for audio applications, with a focus on inference efficiency across NPUs, GPUs, and CPUs. - Perform model evaluation, quantization, and compression to enable fast, robust inference on embedded hardware. - Analyze and compare model architectures (such as Diffusion Models, U-Nets, Transformers, BERT, BART, etc.) for use in audio applications. - Collaborate with cross-functional R&D, systems, and integration teams for system use case verification and commercialization support. - Contribute to the design and software implementation of audio ML models in embedded C/C++ and Python. - Evaluate system performance, debug, and optimize for performance and robustness. - Participate in industry trends, benchmarking and performance analysis of various Model architecture, and bring up-to-date architectural or technical innovations to the team. Requirements: - Strong programming skills in C/C++, Python. - Experience with audio processing and embedded solutions. - Hands-on experience working with audio framework and audio solutions on any platform - Familiarity with ML frameworks (PyTorch, TensorFlow, ONNX, etc.). - Knowledge of model quantization and compression techniques, and experience optimizing inference and deployment on embedded hardware. - Strong understanding of ML model architectures such as, CNNs, RNNs, Transformers, U-Nets, and statistical modeling techniques. - Understanding of DSP or Microcontroller architectures and frameworks - Experience developing and debugging software on embedded platforms; familiarity with software design patterns, multi-threaded programming (e.g., POSIX, PTHREADS), and fixed-point coding. - Excellent verbal and written communication skills; ability to work independently and as a team player in geographically dispersed, multidisciplinary teams. - Proven ability to work in a dynamic, multi-tasked environment "” quick learner, self-motivated, and results-driven. Minimum Qualifications: Bachelors, Masters or PhD in Computer Science, Electronics and Communication, Electrical Engineering, or a related field (or equivalent work experience). Preferred Qualifications: - Experience working with Qualcomm AI HW accelerators (NPUs) and Qualcomm SDKs - Knowledge of Qualcomm Audio framework, platforms and tools Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities: In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements Masters/Bachelors degree in computer science or equivalent.2-4 years of relevant work experience in software development.Strong understanding of Generative AI models- LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU).Strong in C/C++ programming, Design Patterns and OS concepts. Good scripting skills in Python.Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

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)

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

As an AI Engineer, you will have the exciting opportunity to work with companies seeking individuals who are passionate and hands-on in developing and scaling intelligent features directly into their products. In this fast-paced and high-impact role, you will be instrumental in designing machine learning pipelines, fine-tuning models, and seamlessly deploying them. Your responsibilities will include designing, training, and deploying machine learning and deep learning models, such as NLP, vision, or tabular models. You will collaborate closely with product and engineering teams to build end-to-end AI-driven features. Additionally, you will be responsible for building and maintaining data pipelines, monitoring model performance in production environments, researching and implementing cutting-edge techniques to enhance model outcomes, optimizing models for performance and scalability, and ensuring reproducibility and version control of model experiments. To excel in this role, you should have a strong foundation in machine learning and deep learning algorithms. Proficiency in Python and ML libraries like PyTorch, TensorFlow, and Scikit-learn is essential. Experience with model deployment and serving, including REST APIs, ONNX, and TorchScript, will be beneficial. Familiarity with data handling tools such as Pandas and NumPy, as well as workflow tools like MLflow and Airflow, is also required. Strong problem-solving skills and an iterative, experiment-driven mindset are key attributes for success in this position. In terms of qualifications, a minimum of 3-10 years of relevant experience is required. Exposure to additional areas such as LLMs, embeddings, vector databases (e.g., FAISS, Pinecone), MLOps or DevOps workflows, GPT-like models, retrieval-augmented generation (RAG), multimodal systems, cloud platforms (AWS, GCP, or Azure), and streaming data or real-time systems will be considered a bonus. Joining this role offers you high ownership and the opportunity to shape AI-first product experiences. You can expect a fast-paced learning environment with exposure to the entire product lifecycle. The collaborative team setting provides room for growth and leadership opportunities, allowing you to work on cutting-edge ML applications with significant real-world user impact.,

Overview: We are seeking an Embedded AI Software Engineer with deep expertise in writing software for resource-constrained edge hardware. This role is critical to building optimized pipelines that leverage media encoders/decoders, hardware accelerators, and AI inference runtimes on platforms like NVIDIA Jetson, Hailo, and other edge AI SoCs. You will be responsible for developing highly efficient, low-latency modules that run on embedded devices, involving deep integration with NVIDIA SDKs (Jetson Multimedia, DeepStream, TensorRT) and broader GStreamer pipelines. Key Responsibilities: Media Pipeline & AI Model Integration Implement hardware-accelerated video processing pipelines using GStreamer, V4L2, and custom media backends. Integrate AI inference engines using NVIDIA TensorRT, DeepStream SDK, or similar frameworks (ONNX Runtime, OpenVINO, etc.). Profile and optimize model loading, preprocessing, postprocessing, and buffer management for edge runtime. System-Level Optimization Design software within strict memory, compute, and power budgets specific to edge hardware. Utilize multimedia capabilities (ISP, NVENC/NVDEC) and leverage DMA, zero-copy mechanisms where applicable. Implement fallback logic and error handling for edge cases in live deployment conditions. Platform & Driver-Level Work Work closely with kernel modules, device drivers, and board support packages to tune performance. Collaborate with hardware and firmware teams to validate system integration. Contribute to device provisioning, model updates, and boot-up behavior for AI edge endpoints. Required Skills & Qualifications: Educational Background: Bachelor’s or Master’s degree in Computer Engineering, Electronics, Embedded Systems, or related fields. Professional Experience: 2–4 years of hands-on development for edge/embedded systems using C++ (mandatory). Demonstrated experience with NVIDIA Jetson or equivalent edge AI hardware platforms. Technical Proficiency: Proficient in C++11/14/17 and multi-threaded programming. Strong understanding of video codecs, media IO pipelines, and encoder/decoder frameworks. Experience with GStreamer, V4L2, and multimedia buffer handling. Familiarity with TensorRT, DeepStream, CUDA, and NVIDIA’s multimedia APIs. Exposure to other runtimes like HailoRT, OpenVINO, or Coral Edge TPU SDK is a plus. Bonus Points Familiarity with build systems (CMake, Bazel), cross-compilation, and Yocto. Understanding of AI model quantization, batching, and layer fusion for performance. Prior experience working with camera bring-up, video streaming, and inference on live feeds. Contact Information: To apply, please send your resume and portfolio details to hire@condor-ai.com with “Application: Embedded AI Software Engineer” in the subject line. About Condor AI: Condor is an AI engineering company where we use artificial intelligence models to deploy solutions in the real world. Our core strength lies in Edge AI, combining custom hardware with optimized software for fast, reliable, on device intelligence. We work across smart cities, industrial automation, logistics, and security, with a team that brings over a decade of experience in AI, embedded systems, and enterprise grade solutions. We operate lean, think globally, and build for production from system design to scaled deployment.

Ready to shape the future of work? At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory , our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI , 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’s 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 genpact.com and on LinkedIn , X , YouTube , and Facebook . 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—ensuring 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’ll 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’s or Master’s 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’s 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 'starter kit,' paying to apply, or purchasing equipment or training. Job Lead Consultant Primary Location India-Hyderabad Schedule Full-time Education Level Bachelor's / Graduation / Equivalent Job Posting Jul 16, 2025, 3:14:00 AM Unposting Date Ongoing Master Skills List Digital Job Category Full Time

Position - Algorithm / Library Developer Experience - 4+ years Location - Gurgaon (5 Days WFO) If you are interested kindly fill out the form: https://forms.gle/3PxT1tBitCJcbT2i7 About Company: It is a high-impact energy-tech product company enabling utilities to detect, predict, and heal distribution-level grid faults in real time—enhancing reliability, reducing losses, and modernizing power infrastructure using cutting-edge AI-IoT technology. It aims to revolutionizing electricity distribution by transforming traditional grids into smart, connected, and predictive networks . Role Overview : We are seeking an experienced and driven AI/ML Library Developer to spearhead the design, development, and maintenance of cutting-edge libraries in the Artificial Intelligence and Machine Learning space. You will play a key role in building new libraries, updating existing ones, integrating them into production systems, and mentoring junior developers in the team. Key Responsibilities: Design and develop new AI/ML libraries in Python , C/C++ to support scalable, high-performance machine learning workflows. Enhance and maintain existing libraries , ensuring they meet evolving requirements and deliver robust performance. Integrate developed libraries seamlessly with broader application architectures and pipelines. Provide technical mentorship to junior developers, conducting code reviews, pair programming, and knowledge-sharing sessions. Collaborate closely with data scientists, research engineers, and product teams to translate requirements into efficient, well-architected solutions. Develop clear, maintainable documentation for all components, APIs, and workflows. Proactively identify opportunities to improve performance, reliability, and maintainability across the codebase. Required Skills & Qualifications: 3+ years of hands-on experience in C/C++ development, ideally in systems, libraries, or performance-critical components. Strong understanding of AI/ML concepts , algorithms, and deployment workflows (e.g., model training, inference, optimization). Demonstrated experience in developing and maintaining libraries that are consumed by other applications or teams. Proficiency in integrating C/C++ libraries with higher-level languages (e.g., Python, Java) is a plus. Experience in mentoring junior engineers , conducting code reviews, and contributing to best practices. Familiarity with cross-platform development, build systems (CMake, Make), and version control (Git). Excellent problem-solving skills, with a passion for clean, efficient, and well-documented code. Nice to Have: Exposure to CUDA, OpenCL, or other GPU programming frameworks. Experience with modern AI/ML frameworks (TensorFlow, PyTorch, ONNX) and their C/C++ APIs. Knowledge of performance profiling tools and techniques for optimization.

Work Model: Hybrid (One in a week to office) Locations: Chennai, Bengaluru, Gurgaon, Pune Job Purpose: Analyzing, designing, developing, and managing the infrastructure to release scalable Data Science models. The ML Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated, and repeatable way. Job Responsibilities Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to the user requests in near real time. Design and implement the pipelines for training and deployment of ML models. Design dashboards to monitor a system. Collect metrics and create alerts based on them. Design and execute performance tests. Perform feasibility studies/analysis with a critical point of view. Support and maintain (troubleshoot issues with data and applications). Develop technical documentation for applications, including diagrams and manuals. Working on many different software challenges always ensuring a combination of simplicity and maintainability within the code. Contribute to architectural designs of large complexity and size, potentially involving several distinct software components. Mentoring other engineers fostering good engineering practices across the department. Working closely with data scientists and a variety of end-users (across diverse cultures) to ensure technical compatibility and user satisfaction. Work as a member of a team, encouraging team building, motivation and cultivating effective team relations. Role Requirements E=essential, P=preferred P - Bachelor's degree in Computer Science or related field P - Masters degree in data engineering or related E - Demonstrated experience and knowledge in Linux and Docker containers E - Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS) P - Demonstrated experience and knowledge in distributed systems E - Proficient in programming languages: Python E Experience with ML/Ops technologies like Azure ML E Self driving and good communication skills P Experience with AI/ML frameworks: Torch, Onnx, Tensorflow E - Experience designing and implementing CICD pipelines for automation. P - Experience designing monitoring dashboards (Grafana or similar) P - Experience with container orchestrators (Kubernetes, Docker Swarm. E - Experience in using collaborative developing tools such as Git, Confluence, Jira, etc.

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