319 Quantization Jobs - Page 4

AI/ ML Engineer Required exp: 3–5+ Years Experience Location: Mohali, Punjab | Domain: AI/ML | Mode: WFO / WFH ChicMic Studios is looking for a passionate AI/ML Engineer with hands-on experience in Python, Django/Flask, AWS, and modern machine learning frameworks like PyTorch, TensorFlow, and transformers. If building scalable AI applications and deploying real-world ML solutions excite you — we’d love to talk! Key Responsibilities: - Build scalable web apps using Django & Flask - Design APIs using Django Rest Framework (DRF) - Deploy apps on AWS (EC2, S3, Lambda, RDS, etc.) - Integrate and serve AI/ML models (NLP, vision, transformers) - Use TensorFlow, PyTorch, scikit-learn for model development - Work with transformer models like BERT/GPT for NLP tasks - Optimize models (quantization, pruning, hyperparameter tuning) - Deploy using TorchServe, TensorFlow Serving, AWS SageMaker - Collaborate across teams and ensure app & model scalability Required Skills: - 3+ years of professional Python development experience - Strong knowledge of Django, Flask, DRF - Experience with AWS services for deployment - Deep understanding of ML concepts and hands-on with PyTorch/TensorFlow - Worked with SQL/NoSQL databases (PostgreSQL, MongoDB) - Exposure to MLOps practices is a big plus - Bonus: Familiar with front-end basics (HTML, CSS, JS) - Strong team player with problem-solving and communication skills Why Join Us: - 5 Days Working - Great Learning Exposure - EPF Benefit - Earned Leaves - High Employee Retention - Work Across 16+ Technologies Let’s Connect! Email: disha.mehta755@chicmicstudios.in _ Contact: +91 98759 52834 _ _ Visit us: https://www.chicmicstudios.in/ _ Come be part of a team that's redefining innovation through AI. Whether you're an expert or on your way there — we support growth, ownership, and real impact. Job Type: Full-time Pay: ₹600,000.00 - ₹1,500,000.00 per month Benefits: Leave encashment Provident Fund Work from home Schedule: Day shift Monday to Friday Education: Bachelor's (Required) Experience: Python: 3 years (Required) Language: English (Required) Work Location: In person

Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power wireless connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the world’s most highly integrated SoCs, Silicon Labs provides device makers the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over 16 countries and is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. Learn more at www.silabs.com. Meet the Team The Software Research & Development Team in Hyderabad is responsible for developing next-generation software technologies for our IoT portfolio, including Zigbee, Thread, Matter, Wi-Fi, proprietary radio software, and hardware modeling. We are expanding our AI/ML software engineering team in Hyderabad to enable smarter IoT devices by running machine learning (ML) algorithms directly on the edge. These algorithms power applications such as anomaly detection, wake-word recognition, and image classification. Our mission is to bring advanced ML capabilities to resource-constrained devices using cutting-edge optimization techniques and hardware acceleration. As an AI/ML Engineer, you will: Collaborate with engineers and architects to design and implement embedded ML solutions for Silicon Labs’ wireless microcontrollers. Integrate third-party ML frameworks (e.g., ExecuTorch, CMSIS-NN, CMSIS-DSP) into our embedded software stack. Develop optimization techniques to improve model performance on memory- and energy-constrained devices. Contribute to tools for ML model conversion, deployment, and evaluation. Build demo applications and reference examples to showcase edge ML capabilities. Create technical documentation and training resources for internal and external developers. Apply best practices in embedded development, debugging, and ML model deployment. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Electrical/Electronics Engineering, or a related technical field. 4+ years of professional experience in embedded systems software development. Proficiency in C/C++, Python, and Git. Strong understanding of embedded systems development, debugging tools, and cross-compilation. Exposure to machine learning algorithms, including deep neural networks and classical ML methods. Knowledge of ARM microcontrollers (MCUs). Familiarity with digital signal processing (DSP) and embedded ML frameworks like ExecuTorch, CMSIS-NN, or CMSIS-DSP. Strong analytical and communication skills. Eagerness to learn and grow in a fast-paced, collaborative environment. Nice to Have: Experience with ML model training, quantization, and deployment pipelines. Familiarity with real-time operating systems (RTOS). Knowledge of TensorFlow and PyTorch. Experience with Linux and using the command line. Familiarity with project planning and documentation tools like JIRA and Confluence Nice to Have: Experience with ML model training, quantization, and deployment pipelines. Familiarity with real-time operating systems (RTOS). Knowledge of TensorFlow and PyTorch. Experience with Linux and using the command line. Familiarity with project planning and documentation tools like JIRA and Confluence Benefits & Perks: Not only will you be joining a highly skilled and tight-knit team where every engineer makes a significant impact on the product; we also strive for good work/life balance and to make our environment welcoming and fun. Equity Rewards (RSUs) Employee Stock Purchase Plan (ESPP) Insurance plans with Outpatient cover National Pension Scheme (NPS) Flexible work policy Childcare support We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. Silicon Labs is an equal opportunity employer and values the diversity of our employees. Employment decisions are made on the basis of qualifications and job-related criteria without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other characteristic protected by applicable law.

About the Role We are an ambitious technology company building innovative products at the intersection of artificial intelligence, accessibility, and digital content. We are seeking a skilled Machine Learning Engineer to join our team and drive the development of advanced machine learning systems across several high-impact applications. Responsibilities End-to-End ML Development: Design, train, and optimize deep learning models for computer vision, natural language processing, and multimodal data. Develop scalable pipelines for data collection, preprocessing, and augmentation. Implement real-time inference solutions suitable for web and mobile platforms. Research & Prototyping: Evaluate state-of-the-art models and adapt them to our product requirements. Build proof-of-concept systems to validate new ideas and features. Infrastructure & Deployment: Package and deploy models into production environments. Optimize models for latency and performance on resource-constrained devices. Collaboration: Work closely with cross-functional teams, including software engineers, designers, and product managers. Participate in code reviews, documentation, and knowledge sharing. Data Engineering & Infrastructure Build scalable data pipelines to collect, clean, and augment multimodal datasets (video, audio, text) Develop model deployment pipelines for mobile and web (TensorFlow Lite, ONNX, PyTorch Mobile) Integrate ML inference with our React Native, Python, and Node.js backends Applied Research & Prototyping Research state-of-the-art models (Transformers, Diffusion, GANs) and adapt them to Product use cases Develop proof-of-concepts and iterate rapidly with the product and design teams Contribute to model evaluation, A/B testing, and continuous improvement Must-Have Skills Experience in applied ML, deep learning, or computer vision Proficiency in Python, TensorFlow, PyTorch Experience with: CNNs and RNNs for video/sequence tasks NLP models (Transformers, BERT, GPT-style architectures) Real-time inference optimization (TensorRT, quantization, pruning) Strong understanding of data engineering workflows Familiarity with integrating ML into production systems (REST APIs, microservices) Nice-to-Have: Experience with LiDAR or 3D spatial data Familiarity with React Native and mobile ML deployment Contributions to open-source ML projects Publications or patents in ML/AI domains What We Offer: Opportunity to build technologies that fundamentally improve millions of lives A collaborative, purpose-driven environment Competitive salary and performance incentives Full ownership of end-to-end ML systems Access to cutting-edge infrastructure Job Type: Full-time Pay: ₹272,000.00 - ₹400,000.00 per year Benefits: Paid sick time Paid time off Provident Fund Schedule: Monday to Friday Supplemental Pay: Performance bonus Work Location: In person

Job Title: AI Engineer – Computer Vision (Onsite/Remote, Full-Time) Location: Remote/Onsite – Chennai Duration: Full Time Experience: 1-5 years preferred Package: Up to 9LPA (Based on Experience) Role Overview: As an AI Engineer, you’ll lead the design, development, and deployment of advanced computer vision models for human motion understanding and video analytics. You'll work across the full lifecycle of AI development — from data pipelines to inference optimization — helping ship features that power our next-generation fitness intelligence systems. This is a high-impact, engineering-heavy role with a strong focus on real-world deployment, performance, and scale — not academic prototyping. Key Responsibilities: 1. Own the end-to-end lifecycle of computer vision models: from experimentation to deployment and monitoring. 2. Build and optimize deep learning models (YOLOv8, Vision Transformers, EfficientNet, SlowFast, I3D) for: i. ii. iii. Pose estimation and skeleton tracking Activity recognition and classification Posture correction and rep counting 3. Apply transfer learning, fine-tuning, and knowledge distillation techniques for performance and generalization. 4. Design scalable pipelines for video data ingestion, annotation, preprocessing, and augmentation. 5. Integrate AI modules into cloud-based (Azure/AWS) environments using REST APIs or microservices. 6. Optimize model inference using ONNX, TensorRT, and quantization strategies for real-time or edge deployment. 7. Collaborate cross-functionally with product, design, and frontend/backend teams to align on deliverables and timelines. 8. Stay up to date with the latest in vision research and evaluate new techniques for production integration. Required Skills: 1. Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related discipline. 2. 2+ years of experience building and deploying computer vision models in production environments. 3. Proficient in Python, with deep experience in PyTorch and/or TensorFlow. 4. Hands-on expertise in models such as: a. YOLOv5/YOLOv8 b. Vision Transformers (ViT, TimeSformer) o ResNet, EfficientNet o SlowFast, I3D, UNet 5. Experience working with pose estimation frameworks (Mediapipe, OpenPose, Detectron2). 6. Strong understanding of camera calibration, 3D geometry, and real-time motion tracking. 7. Experience integrating models into cloud environments (Azure, AWS) using APIs or containers. 8. Familiarity with tools such as OpenCV, MMAction2, DeepSort, and ONNX/TensorRT. Preferred Skills: Experience in real-time video analytics, edge AI, and system optimization. Familiarity with CI/CD pipelines, Docker, and monitoring tools for deployed models. Prior experience in the fitness or healthcare domain with time-series or movement data. Strong grasp of system-level design: latency tradeoffs, hardware acceleration, and scalability. What You’ll Gain A key role in shaping the next generation of intelligent fitness systems. Flexible work environment with learning and mentorship. Autonomy, ownership, and the opportunity to deploy models used by real users. A fast-paced environment with exposure to the full AI pipeline, from data to deployment. Collaborative team culture with a focus on engineering excellence and innovation. Job Type: Full-time Pay: ₹500,000.00 - ₹900,000.00 per year Benefits: Health insurance Schedule: Fixed shift Work Location: In person Expected Start Date: 15/07/2025

AI/ ML Engineer Required exp: 3–5+ Years Experience Location: Mohali, Punjab | Domain: AI/ML | Mode: WFO / WFH ChicMic Studios is looking for a passionate AI/ML Engineer with hands-on experience in Python, Django/Flask, AWS, and modern machine learning frameworks like PyTorch, TensorFlow, and transformers. If building scalable AI applications and deploying real-world ML solutions excite you — we’d love to talk! Key Responsibilities: - Build scalable web apps using Django & Flask - Design APIs using Django Rest Framework (DRF) - Deploy apps on AWS (EC2, S3, Lambda, RDS, etc.) - Integrate and serve AI/ML models (NLP, vision, transformers) - Use TensorFlow, PyTorch, scikit-learn for model development - Work with transformer models like BERT/GPT for NLP tasks - Optimize models (quantization, pruning, hyperparameter tuning) - Deploy using TorchServe, TensorFlow Serving, AWS SageMaker - Collaborate across teams and ensure app & model scalability Required Skills: - 3+ years of professional Python development experience - Strong knowledge of Django, Flask, DRF - Experience with AWS services for deployment - Deep understanding of ML concepts and hands-on with PyTorch/TensorFlow - Worked with SQL/NoSQL databases (PostgreSQL, MongoDB) - Exposure to MLOps practices is a big plus - Bonus: Familiar with front-end basics (HTML, CSS, JS) - Strong team player with problem-solving and communication skills Why Join Us: - 5 Days Working - Great Learning Exposure - EPF Benefit - Earned Leaves - High Employee Retention - Work Across 16+ Technologies Let’s Connect! Email: disha.mehta755@chicmicstudios.in _ Contact: +91 98759 52834 _ _ Visit us: https://www.chicmicstudios.in/ _ Come be part of a team that's redefining innovation through AI. Whether you're an expert or on your way there — we support growth, ownership, and real impact. Job Type: Full-time Pay: ₹600,000.00 - ₹1,500,000.00 per month Benefits: Leave encashment Provident Fund Work from home Schedule: Day shift Monday to Friday Education: Bachelor's (Required) Experience: Python: 3 years (Required) Language: English (Required) Work Location: In person

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Job Description 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: Master’s/Bachelor’s 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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from 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.

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary Job Description 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 Master’s/Bachelor’s 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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from 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. 3077906

AI/ML Engineer / Data Scientist Company: Triumph Edge Innovations Pvt. Ltd. Location: Ernakulam , Kerala, India Job Type: Full-time, Part time About Triumph Edge: Triumph Edge is a leading Indian technology firm dedicated to providing cutting-edge AI-Powered Image Analysis (AI-PIA) solutions for India's defense sector. In alignment with the "Atmanirbhar Bharat" and "Make in India" initiatives, we are committed to building indigenously developed, state-of-the-art AI systems for Intelligence, Surveillance, and Reconnaissance (ISR). Our mission is to empower our armed forces with efficient, secure, and actionable intelligence, contributing directly to national security. Job Summary: As an AI/ML Engineer / Data Scientist at Triumph Edge, you will be an integral part of our R&D team, responsible for designing, developing, and deploying advanced AI-powered image analysis systems for defence applications. You will have a direct impact on building and optimizing models that can analyse large-scale visual datasets, detect threats, and enhance situational awareness. We are seeking individuals passionate about national security and capable of solving complex challenges using cutting-edge AI technologies. Key Responsibilities and Duties: AI/ML Model Development: Design, train, and evaluate state-of-the-art Deep Learning and Computer Vision models for critical defence requirements (e.g., object detection, classification, tracking, change detection, anomaly detection, facial recognition). Work extensively with various neural network architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. Continuously improve model performance, accuracy, and efficiency across diverse operational environments (e.g., varying lighting, weather conditions, terrain types). Explore and integrate Generative AI (GenAI) models where applicable for tasks like synthetic data generation or image enhancement. Data Engineering & Preprocessing: Collect, clean, label, and preprocess large-scale image and video datasets (including satellite imagery, drone footage, and ground sensor data). Develop and maintain robust data pipelines for efficient data ingestion, transformation, and preparation for AI model training and evaluation. Ensure the quality, integrity, and security of sensitive defense-related data. Algorithm Optimisation & Deployment: Optimize AI models for efficient deployment on resource-constrained edge devices (e.g., drones, ground sensors) and high-performance computing (HPC) environments for real-time inference. Implement techniques such as model compression, quantization, and inference optimization to enhance performance on target hardware. Monitor and maintain the performance of deployed AI models in production environments. Research and Innovation: Stay abreast of the latest research trends and advancements in Machine Learning, Deep Learning, and Computer Vision, particularly those relevant to the defense domain. Conduct experimental research and develop innovative solutions to address complex, real-world challenges in defense intelligence. Contribute to intellectual property generation, including patents and research publications. Team Collaboration: Collaborate effectively with cross-functional teams, including Software Engineers, Data Engineers, DevOps Engineers, and Defence Domain Experts, to integrate AI solutions into larger systems. Clearly communicate complex technical concepts, findings, and recommendations to both technical and non-technical stakeholders. Participate in code reviews, knowledge sharing sessions, and contribute to a collaborative R&D culture. Security & Compliance: Adhere to stringent cybersecurity protocols and secure coding practices for all AI model development and deployment. Ensure compliance with relevant Indian defense regulations and data security standards. Required Qualifications & Skills: Education: Master's degree (M.Tech/MS) or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field. Experience: [Specify preferred years of experience, e.g., 2+ years for Mid-level, 5+ years for Senior-level] of hands-on experience in AI/ML model development, specifically in Computer Vision. Proven experience in building and deploying Deep Learning models for real-world applications. Technical Proficiency: Programming Languages: Expert-level proficiency in Python, with extensive experience using scientific computing libraries (NumPy, Pandas, Scikit-learn). Proficiency in C++ is a significant advantage for high-performance applications. Deep Learning Frameworks: Strong hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch). Computer Vision Libraries/Techniques: In-depth knowledge and practical experience with OpenCV, and familiarity with various computer vision algorithms (e.g., object detection models like YOLO, Faster R-CNN; segmentation, tracking algorithms). Data Management: Experience with data cleaning, feature engineering, and working with large datasets. Familiarity with SQL and/or NoSQL databases is a plus. Cloud Platforms: Experience with cloud computing platforms (AWS, Azure, or GCP) for AI model training and deployment is desirable. Problem-Solving: Excellent analytical and problem-solving skills, with a strong ability to translate complex defence requirements into effective AI solutions. Learning Agility: Eagerness to learn new technologies, adapt to evolving research trends, and continuously improve technical skills. Communication: Strong verbal and written communication skills, capable of articulating technical concepts clearly. Preferred Qualifications (Bonus Points): Prior experience working on projects related to the defense sector, aerospace, or intelligence agencies. Familiarity with specific Indian defence regulations or standards. Experience with MLOps practices for deploying and managing AI models in production. Knowledge of explainable AI (XAI) techniques. Publications in top-tier AI/ML/Computer Vision conferences or journals. Experience with GPU optimisation (CUDA programming). Why Join Triumph Edge? Impactful Work: Contribute directly to strengthening India's national security and the "Atmanirbhar Bharat" initiative. Cutting-Edge Technology: Work on highly advanced AI and Deep Learning problems with real-world applications in defence. Innovation Culture: Be part of a dynamic R&D team that fosters creativity, continuous learning, and groundbreaking research. Growth Opportunities: Grow your career in a rapidly expanding sector with significant opportunities for professional development. Collaborative Environment: Work alongside brilliant minds, including experienced AI researchers, engineers, and defence domain experts. To Apply: Interested candidates are invited to submit their resume and a cover letter detailing their relevant experience and interest in this role. Job Types: Part-time, Permanent, Internship, Contractual / Temporary, Freelance Contract length: 36 months Pay: ₹266,866.36 - ₹1,794,918.81 per year Expected hours: 30 per week Benefits: Cell phone reimbursement Work Location: In person

AI/ML Engineer / Data Scientist Company: Triumph Edge Innovations Pvt. Ltd. Location: Ernakulam , Kerala, India Job Type: Full-time, Part time About Triumph Edge: Triumph Edge is a leading Indian technology firm dedicated to providing cutting-edge AI-Powered Image Analysis (AI-PIA) solutions for India's defense sector. In alignment with the "Atmanirbhar Bharat" and "Make in India" initiatives, we are committed to building indigenously developed, state-of-the-art AI systems for Intelligence, Surveillance, and Reconnaissance (ISR). Our mission is to empower our armed forces with efficient, secure, and actionable intelligence, contributing directly to national security. Job Summary: As an AI/ML Engineer / Data Scientist at Triumph Edge, you will be an integral part of our R&D team, responsible for designing, developing, and deploying advanced AI-powered image analysis systems for defence applications. You will have a direct impact on building and optimizing models that can analyse large-scale visual datasets, detect threats, and enhance situational awareness. We are seeking individuals passionate about national security and capable of solving complex challenges using cutting-edge AI technologies. Key Responsibilities and Duties: AI/ML Model Development: Design, train, and evaluate state-of-the-art Deep Learning and Computer Vision models for critical defence requirements (e.g., object detection, classification, tracking, change detection, anomaly detection, facial recognition). Work extensively with various neural network architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. Continuously improve model performance, accuracy, and efficiency across diverse operational environments (e.g., varying lighting, weather conditions, terrain types). Explore and integrate Generative AI (GenAI) models where applicable for tasks like synthetic data generation or image enhancement. Data Engineering & Preprocessing: Collect, clean, label, and preprocess large-scale image and video datasets (including satellite imagery, drone footage, and ground sensor data). Develop and maintain robust data pipelines for efficient data ingestion, transformation, and preparation for AI model training and evaluation. Ensure the quality, integrity, and security of sensitive defense-related data. Algorithm Optimisation & Deployment: Optimize AI models for efficient deployment on resource-constrained edge devices (e.g., drones, ground sensors) and high-performance computing (HPC) environments for real-time inference. Implement techniques such as model compression, quantization, and inference optimization to enhance performance on target hardware. Monitor and maintain the performance of deployed AI models in production environments. Research and Innovation: Stay abreast of the latest research trends and advancements in Machine Learning, Deep Learning, and Computer Vision, particularly those relevant to the defense domain. Conduct experimental research and develop innovative solutions to address complex, real-world challenges in defense intelligence. Contribute to intellectual property generation, including patents and research publications. Team Collaboration: Collaborate effectively with cross-functional teams, including Software Engineers, Data Engineers, DevOps Engineers, and Defence Domain Experts, to integrate AI solutions into larger systems. Clearly communicate complex technical concepts, findings, and recommendations to both technical and non-technical stakeholders. Participate in code reviews, knowledge sharing sessions, and contribute to a collaborative R&D culture. Security & Compliance: Adhere to stringent cybersecurity protocols and secure coding practices for all AI model development and deployment. Ensure compliance with relevant Indian defense regulations and data security standards. Required Qualifications & Skills: Education: Master's degree (M.Tech/MS) or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field. Experience: [Specify preferred years of experience, e.g., 2+ years for Mid-level, 5+ years for Senior-level] of hands-on experience in AI/ML model development, specifically in Computer Vision. Proven experience in building and deploying Deep Learning models for real-world applications. Technical Proficiency: Programming Languages: Expert-level proficiency in Python, with extensive experience using scientific computing libraries (NumPy, Pandas, Scikit-learn). Proficiency in C++ is a significant advantage for high-performance applications. Deep Learning Frameworks: Strong hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch). Computer Vision Libraries/Techniques: In-depth knowledge and practical experience with OpenCV, and familiarity with various computer vision algorithms (e.g., object detection models like YOLO, Faster R-CNN; segmentation, tracking algorithms). Data Management: Experience with data cleaning, feature engineering, and working with large datasets. Familiarity with SQL and/or NoSQL databases is a plus. Cloud Platforms: Experience with cloud computing platforms (AWS, Azure, or GCP) for AI model training and deployment is desirable. Problem-Solving: Excellent analytical and problem-solving skills, with a strong ability to translate complex defence requirements into effective AI solutions. Learning Agility: Eagerness to learn new technologies, adapt to evolving research trends, and continuously improve technical skills. Communication: Strong verbal and written communication skills, capable of articulating technical concepts clearly. Preferred Qualifications (Bonus Points): Prior experience working on projects related to the defense sector, aerospace, or intelligence agencies. Familiarity with specific Indian defence regulations or standards. Experience with MLOps practices for deploying and managing AI models in production. Knowledge of explainable AI (XAI) techniques. Publications in top-tier AI/ML/Computer Vision conferences or journals. Experience with GPU optimisation (CUDA programming). Why Join Triumph Edge? Impactful Work: Contribute directly to strengthening India's national security and the "Atmanirbhar Bharat" initiative. Cutting-Edge Technology: Work on highly advanced AI and Deep Learning problems with real-world applications in defence. Innovation Culture: Be part of a dynamic R&D team that fosters creativity, continuous learning, and groundbreaking research. Growth Opportunities: Grow your career in a rapidly expanding sector with significant opportunities for professional development. Collaborative Environment: Work alongside brilliant minds, including experienced AI researchers, engineers, and defence domain experts. To Apply: Interested candidates are invited to submit their resume and a cover letter detailing their relevant experience and interest in this role. Job Types: Part-time, Permanent, Internship, Contractual / Temporary, Freelance Contract length: 36 months Pay: ₹266,866.36 - ₹1,794,918.81 per year Expected hours: 30 per week Benefits: Cell phone reimbursement Work Location: In person

We’re looking for a hands-on backend expert who can take our FastAPI-based platform to the next level: production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. WHAT YOU'LL BUILD 1. Core Backend Enhancements Build APIs Harden security (OAuth2/JWT, rate-limiting, SecretManager) and observability (structured logging, tracing) Add CI/CD, test automation, ,health checks and SLO dashboards 2. Awesome UI Interfaces React.js/Next.js, Redact/Context, Tailwind / MUI / Custom-CSS / Shadcn / Axios 3. LLM & Agentic Services Design micro/mini-services that host and route to OpenAI, Anthropic, local HF models, embeddings & RAG pipelines Implement autonomous/recursive agents that orchestrate multi-step chains (Tools, Memory, Planning) 4. Model-Inference Infrastructure Spin up GPU / CPU inference servers behind an API gateway Optimize throughput with batching, streaming, quantization & caching (Redis / pgvector) 5. NLP & Data Services Own the NLP stack: Transformers for classification, extraction, and embedding generation. Build data pipelines that join aggregated business metrics with model telemetry for analytics TECH STACK YOU'LL WORK WITH 1.Fullstack/Backend Infrastructure • Python, FastAPI, Starlette, Pydantic • Async SQLAlchemy, Postgres, Alembic, pgvector • Docker, Kubernetes, or ECS/Fargate - AWS (Or) GCP • Redis / RabbitMQ / Celery (jobs & caching) • Prometheus, Grafana, OpenTelemetry • If you are a full-stack person, then - react.js / next.js / shadcn / tailwind.css / MUI 2.AI / NLP • HuggingFace Transformers, LangChain / Llama-Index, Torch / TensorRT • OpenAI, Anthropic, Azure OpenAI, Cohere APIs • Vector search (Pinecone, Qdrant, PGVector) 3. Tooling • Pytest, GitHub Actions • Terraform / CDK preferred MUST HAVE EXPERIENCE • 3+ yrs building production Python REST APIs (FastAPI, Flask, or Django-REST) • SQL schema design & query optimization in Postgres (CTEs, JSONB) • Deep knowledge of async patterns & concurrency (asyncio, AnyIO, celery) • Crafted awesome UI Applications that integrate with the backend API • Hands-on with RAG, LLM/embedding workflows, prompt-engineering & at least one of “agent-ops” frameworks (LangGraph, CrewAI, AutoGen) • Cloud container orchestration (Any of K8s, ECS, GKE, AKS, etc.) • CI/CD pipelines and infra-as-code NICE-TO-HAVE EXPERIENCE • Streaming protocols (Server-Sent Events, WebSockets, gRPC) • NGINX Ingress / AWS API Gateway • RBAC / multi-tenant SaaS security hardening • Data privacy, PII redaction, secure key vault integrations • Bitemporal or event-sourced data models WHY DOES THIS ROLE MATTER? We’re growing fast. Products are live, but evolving. Challenges are real, and the opportunity to own systems end-to-end is massive. You’ll lead how we scale AI services, work directly with the founder, and shape what the next wave of our platform looks like. If you’re looking for meaningful ownership and a chance to work on hard, forward-looking problems, this role is for you.

Job Requirements Design and Development: Design and implement AI/ML-based applications tailored for embedded and edge hardware. Develop end-to-end pipelines for model training, conversion, and deployment. Customize neural network architectures for edge-specific applications such as object detection, classification, and segmentation. Model Optimization and Deployment: Port and optimize AI models to meet performance and memory constraints on edge platforms. Apply quantization (e.g., INT8), pruning, and layer fusion techniques to improve model efficiency. Convert models between various formats such as ONNX, TensorRT, TVM, TFLite, and DRP-AI. Performance Tuning and Profiling: Analyze model bottlenecks and tune for latency, throughput, and power efficiency. Run inference performance profiling on hardware targets and iterate for improvements. Testing and Debugging: Validate model accuracy and performance post-optimization. Debug and troubleshoot model behavior discrepancies across frameworks and devices. Documentation and Research: Maintain documentation for all model lifecycle stages and optimization steps. Stay updated with latest AI compiler advancements and deployment trends in edge AI. Work Experience Must Have : Bachelor's/Master’s degree in Computer Science, Electronics, or AI-related field. 6+ years in AI/ML model development with experience in real-world applications. Proficient in Python, C++ and deep learning libraries (TensorFlow, PyTorch, Keras). Solid understanding of CNNs, FCNs, and their applications in computer vision. Practical knowledge of model optimization workflows (quantization, pruning, etc.). Experience with ONNX, TVM, TensorRT, DRP-AI, TFLite, OpenCV, etc. Experience with deployment on edge devices like Jetson, RZ/V2H, or STM32. Strong understanding of constraints (compute, memory, power) in edge environments. Good to Have: Exposure to embedded Linux or RTOS environments. Familiarity with low-level model debugging, calibration tools, and inference engines. Experience with Continuous Integration tools such as Git, Jenkins, or similar. Understanding of hardware accelerators (GPU, NPU, DRP-AI, etc.).

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Qualcomm’s 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: Bachelor’s, Master’s 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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from 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 Description: We are looking for a highly skilled AI/ML Engineer who can design, implement, and optimize machine learning solutions, including traditional models, deep learning architectures, and generative AI systems. The ideal candidate will have strong hands-on experience with MLOps, data pipelines, and LLM optimization. You will collaborate with data engineers and cross-functional teams to develop scalable, ethical, and high-performance AI/ML solutions that drive business impact. Requirements: Key Responsibilities: Develop, implement, and optimize AI/ML models using both traditional machine learning and deep learning techniques. Design and deploy generative AI models for innovative business applications. Collaborate with data engineers to build and maintain high-quality data pipelines and preprocessing workflows. Integrate responsible AI practices to ensure ethical, explainable, and unbiased model behavior. Develop and maintain MLOps workflows to streamline training, deployment, monitoring, and continuous integration of ML models. Optimize large language models (LLMs) for efficient inference, memory usage, and performance. Work closely with product managers, data scientists, and engineering teams to integrate AI/ML into core business processes. Conduct rigorous testing, validation, and benchmarking of models to ensure accuracy, reliability, and robustness. Stay abreast of the latest research and advancements in AI/ML, LLMs, MLOps, and generative models. Required Skills & Qualifications: Strong foundation in machine learning, deep learning, and statistical modeling techniques. Hands-on experience with TensorFlow, PyTorch, scikit-learn, or similar ML frameworks. Proficient in Python and ML engineering tools such as MLflow, Kubeflow, or SageMaker. Experience deploying generative AI solutions, including text, image, or audio generation. Understanding of responsible AI concepts, including fairness, accountability, and transparency in model building. Solid experience with MLOps pipelines and continuous delivery of ML models. Proficiency in optimizing transformer models or LLMs for production workloads. Familiarity with cloud services (AWS, GCP, Azure) and containerized deployments (Docker, Kubernetes). Excellent problem-solving and communication skills. Ability to work collaboratively with cross-functional teams. Preferred Qualifications: Experience with data versioning tools like DVC or LakeFS. Exposure to vector databases and retrieval-augmented generation (RAG) pipelines. Knowledge of prompt engineering, fine-tuning, and quantization techniques for LLMs. Familiarity with Agile workflows and sprint-based delivery. Contributions to open-source AI/ML projects or published papers in conferences/journals. About Company / Benefits: Lucent Innovation is a company 8 years old, India's premier IT solutions provider company that offers web & web application development services to global clients. We are Shopify Expert and Shopify Plus Partner, have its office registered in India. Lucent Innovation has a highly skilled team of IT professionals. We ensure that our employees have a work-life balance. In order to achieve the same, We work 5 days working, no night shift and employees are encouraged to report to the office on time and leave on time. The company organizes several indoor/outdoor activities throughout the year. Besides these, the company organizes trips for employees. Celebrations are an integral part of our work culture. We celebrate all major festivals like Diwali, Holi, Lohri, Christmas day, Navratra (Dandia), Makar Sankranti etc. We also enjoy several other important occasions like New Year, Independence Day, Republic Day, Women's Day, Mother's day, etc. Perks: - 5days working Flexible working hours No hidden policy Friendly working Environment In-house training Quarterly and Yearly rewards & Appreciation

📍 Location: Ahmedabad (Hybrid Preferred) 🕒 Type: Full-time / Internship About Vakta AI Vakta AI is building a bold new interface to knowledge — through hyper-realistic AI avatars that people can talk to, learn from, and take guidance from in real-time. From intelligent tutors and language coaches to career, legal, and health advisors — we're rethinking how India learns and solves problems, one conversation at a time. We’re assembling a world-class AI team to push the frontiers of LLMs, speech technology, and virtual agent design — blending cutting-edge research with real-world scale. As part of this journey, we’re hiring across core AI/ML roles — a rare chance to shape the future of avatar-based learning and expert access for millions across Bharat. What You’ll Work On Core R&D Fine-tune and optimize LLMs (Mistral, Gemma, Phi, etc.) for interactive, role-based conversations Build voice-driven interfaces using models like Whisper, Bark, OpenVoice, etc. Experiment with LoRA, QLoRA, RAG, quantization, and other performance techniques Engineering & Deployment Convert research into production-grade APIs or on-device models Optimize models for latency, memory, and multilingual support Integrate models with 3D avatar systems and real-time user experiences Internal Knowledge Sharing Maintain clean experiment logs and model documentation Collaborate in internal demos, peer reviews, and quick iteration cycles You Should Have 1–2 years of experience in AI/ML, NLP, or speech tech — or strong project portfolio Proficiency with PyTorch, Transformers, HuggingFace, and model fine-tuning Familiarity with LLM training techniques like LoRA, DPO, RAG, or quantization Hands-on experience with speech technologies (ASR/TTS) is a strong plus Clear communication and the ability to own projects end-to-end Bonus If You’ve Worked On Indian language support / multilingual AI ONNX, model compression, or edge deployment Unity, WebXR, or avatar integration pipelines Open-source contributions or public demos/projects Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related fields Strong academic or project background in NLP, deep learning, or speech processing Alternatively, a solid portfolio of personal/independent work in LLMs or applied ML can substitute for formal education Why Join Vakta AI Build at the intersection of LLMs, speech, and 3D avatars Early-stage team with high ownership and creative freedom Solve real, Bharat-scale education and access problems Work out of Ahmedabad with a hybrid and flexible setup Your work goes live in weeks — not quarters

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Qualcomm’s 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: Bachelor’s, Master’s 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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from 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. 3078103

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary Job Description 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 Master’s/Bachelor’s 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 : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from 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. 3077588

Job Title: AI Lead – Generative AI & ML Systems Key Responsibilities Generative AI Development Design and implement LLM-powered solutions and generative AI models for use cases such as predictive analytics, automation workflows, anomaly detection, and intelligent systems. · RAG & LLM Applications Build and deploy Retrieval-Augmented Generation (RAG) pipelines, structured generation systems, and chat-based assistants tailored to business operations. Full AI Lifecycle Management Lead the complete AI lifecycle—from data ingestion and preprocessing to model design, training, testing, deployment, and continuous monitoring. · Optimization & Scalability Develop high-performance AI/LLM inference pipelines, applying techniques like quantization, pruning, batching, and model distillation to support real-time and memory-constrained environments. MLOps & CI/CD Automation Automate training and deployment workflows using Terraform, GitLab CI, GitHub Actions, or Jenkins, integrating model versioning, drift detection, and compliance monitoring. Cloud & Deployment Deploy and manage AI solutions using AWS, Azure, or GCP with containerization tools like Docker and Kubernetes. AI Governance & Compliance Ensure model/data governance and adherence to regulatory and ethical standards in production AI deployments. Stakeholder Collaboration Work cross-functionally with product managers, data scientists, and engineering teams to align AI outputs with real-world business goals. Required Skills & Qualifications Bachelor’s degree (B.Tech or higher) in Computer Science, IT, or a related field is required. 8-12 Year exp- from the Ai team with overall experience in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) solution development. Minimum 2+ years of hands-on experience in Generative AI and LLM-based solutions, including prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG) pipelines with full CI/CD integration, monitoring, and observability pipelines, with 100% independent contribution. Proven expertise in both open-source and proprietary Large Language Models (LLMs), including LLaMA, Mistral, Qwen, GPT, Claude, and BERT. Expertise in C/C++ & Python programming with relevant ML/DL libraries including TensorFlow, PyTorch, and Hugging Face Transformers. Experience deploying scalable AI systems in containerized environments using Docker and Kubernetes. Deep understanding of the MLOps/LLMOps lifecycle, including model versioning, deployment automation, performance monitoring, and drift detection. Familiarity with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) and DevOps for ML workflows. Working knowledge of Infrastructure-as-Code (IaC) tools like Terraform for cloud resource provisioning and reproducible ML pipelines. Hands-on experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Designed and documented High-Level Design (HLD) and Low-Level Design (LLD) for ML/GenAI systems, covering data pipelines, model serving, vector search, and observability layers. Documentation included component diagrams, network architecture, CI/CD workflows, and tabulated system designs. Provisioned and managed ML infrastructure using Terraform, including compute clusters, vector databases, and LLM inference endpoints across AWS, GCP, and Azure. Experience beyond notebooks: shipped models with logging, tracing, rollback mechanisms, and cost control strategies. Hands-on ownership of production-grade LLM workflows, not limited to experimentation. Full CI/CD integration, monitoring, and observability pipelines, with 100% independent contribution. Preferred Qualifications (Good To Have) Experience with LangChain, LlamaIndex, AutoGen, CrewAI, OpenAI APIs, or building modular LLM agent workflows. Exposure to multi-agent orchestration, tool-augmented reasoning, or Autonomous AI agents and agentic communication patterns with orchestration. Experience deploying ML/GenAI systems in regulated environments, with established governance, compliance, and Responsible AI frameworks. Familiarity with AWS data and machine learning services, including Amazon SageMaker, AWS Bedrock, ECS/EKS, and AWS Glue, for building scalable, secure data pipelines and deploying end-to-end AI/ML workflows.

Current Openings Software Engineer - AI/ML Software Engineer - AI/ML Experience : 2 - 4 years Bhubaneswar Apply About The Job Featured As an AI/ML Engineer, you will be responsible for designing, validating, and integrating cutting-edge machine learning models and algorithms. Collaborate closely with cross-functional teams, including data scientists, to recognize and establish project objectives. Oversee data infrastructure maintenance, ensuring streamlined and scalable data operations. Stay updated with advancements in AI and propose their integration for operational enhancement. Effectively convey detailed data insights to non-technical stakeholders. Uphold stringent data privacy and security protocols. Engage in the full lifecycle of AI projects, spanning from ideation through deployment and continuous upkeep. Core Responsibilities Develop, validate, and implement machine learning models and algorithms. Collaborate with data scientists and other stakeholders to understand and define project goals. Maintain data infrastructure and ensure scalability and efficiency of data-related operations. Stay abreast of the latest developments in the field of AI/Client and recommend ways to implement them in our operations. Communicate complex data findings in a clear and understandable manner to non-technical stakeholders. Adhere to data privacy and security guidelines. Participate in the entire AI project lifecycle, from concept to deployment and maintenance. Required Skills Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals. Solid theoretical understanding of machine learning. Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, bandwidth, and compute. Experience with Vector databases like Chroma Db, Pinecone, PGVector or similar Experience with Large language Models like GPT 3.5, GPT 4, GPT 4.o, Llama, Gemini, Mistral etc. Experience in LLM integration framework like langchain, Llamaindex, AgentGPT etc Experience with ML Models from definition to deployment, including training, quantization, sparsity, model preprocessing, and deployment. Proficiency in Python development in a Linux environment and using standard development tools. Experience with deep learning frameworks (such as PyTorch, Tensorflow, Keras, Spark). Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). Experience in training, tuning, and deploying ML models for Computer Vision (e.g., ResNet), and/or Recommendation Systems (e.g., DLRM). Experience deploying ML workloads on distributed systems. Self-motivated team player with a strong sense of ownership and leadership. Strong verbal, written, and organizational skills for effective communication and documentation. Research background with a publication record. Work experience at a cloud provider or AI compute/sub-system company. Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud. Experience with information security and secure development best practices. Qualifications Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field. 2-4 yrs of hands-on experience in AI/ML Apply

Job Overview We are seeking a highly experienced and innovative Senior AI Engineer with a strong background in Generative AI , including LLM fine-tuning and prompt engineering . This role requires hands-on expertise across NLP , Computer Vision , and AI agent-based systems , with the ability to build, deploy, and optimize scalable AI solutions using modern tools and frameworks. Required Skills & Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related field. 5+ years of hands-on experience in AI/ML solution development. Proven expertise in fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, GPT-family) using techniques like LoRA, QLoRA, PEFT. Deep experience in prompt engineering, including zero-shot, few-shot, and retrieval-augmented generation (RAG). Proficient in key AI libraries and frameworks: LLMs & GenAI: Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Diffusers NLP: SpaCy, NLTK. Vision: OpenCV, MMDetection, YOLOv5/v8, Detectron2 MLOps: MLflow, FastAPI, Docker, Git Familiarity with vector databases (Pinecone, FAISS, Weaviate) and embedding generation. Experience with cloud platforms like AWS, GCP, or Azure, and deployment on in house GPU-backed infrastructure. Strong communication skills and ability to convert business problems into technical solutions. Preferred Qualifications Experience building multimodal systems (text + image, etc.) Practical experience with agent frameworks for autonomous or goal-directed AI. Familiarity with quantization, distillation, or knowledge transfer for efficient model deployment. Key Responsibilities Design, fine-tune, and deploy generative AI models (LLMs, diffusion models, etc.) for real-world applications. Develop and maintain prompt engineering workflows, including prompt chaining, optimization, and evaluation for consistent output quality. Build NLP solutions for Q&A, summarization, information extraction, text classification, and more. Develop and integrate Computer Vision models for image processing, object detection, OCR, and multimodal tasks. Architect and implement AI agents using frameworks such as LangChain, AutoGen, CrewAI, or custom pipelines. Collaborate with cross-functional teams to gather requirements and deliver tailored AI-driven features. Optimize models for performance, cost-efficiency, and low latency in production. Continuously evaluate new AI research, tools, and frameworks and apply them where relevant. Mentor junior AI engineers and contribute to internal AI best practices and documentation. Skills:- Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Large Language Models (LLM), Prompt engineering, Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), Computer Vision, AI Agents, Vector database, Python, Docker and API

Highly skilled Senior Machine Learning Engineer with expertise in Deep Learning, Large Language Models (LLMs), and MLOps/LLMOps to design, optimize, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience in developing and scaling deep learning models, fine-tuning LLMs/ (e.g., GPT, Llama), and implementing robust deployment pipelines for production environments. Responsibilities Model Development & Fine-Tuning: - Design, train, fine-tune and optimize deep learning models (CNNs, RNNs, Transformers) for NLP, computer vision, or multimodal applications. - Fine-tune and adapt Large Language Models (LLMs) for domain-specific tasks (e.g., text generation, summarization, semantic similarity). - Experiment with RLHF (Reinforcement Learning from Human Feedback) and other alignment techniques. Deployment & Scalability (MLOps/LLMOps): - Build and maintain end-to-end ML pipelines for training, evaluation, and deployment. - Deploy LLMs and deep learning models in production environments using frameworks like FastAPI, vLLM, or TensorRT. - Optimize models for low-latency, high-throughput inference (eg., quantization, distillation, etc.). - Implement CI/CD workflows for ML systems using tools like MLflow, Kubeflow. Monitoring & Optimization: - Set up logging, monitoring, and alerting for model performance (drift, latency, accuracy). - Work with DevOps teams to ensure scalability, security, and cost-efficiency of deployed models. Required Skills & Qualifications: - 5-7 years of hands-on experience in Deep Learning, NLP, and LLMs. - Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, and LLM frameworks. - Experience with model deployment tools (Docker, Kubernetes, FastAPI). - Knowledge of MLOps/LLMOps best practices (model versioning, A/B testing, canary deployments). - Familiarity with cloud platforms (AWS, GCP, Azure). Preferred Qualifications: - Contributions to open-source LLM projects.

We are looking for experienced data scientists, who have the aspirations and appetite for working in a start-up environment, and with relevant industry experience to make a significant contribution to our platform and solutions. Primary focus would be to apply machine learning techniques for data extraction from documents from variety of formats including scans and handwritten documents. Responsibilities: Develop a learning model for high accuracy extraction and validation of documents, e.g. in mortgage industry Work with state-of-the-art language modelling approaches such as transformer-based architectures while integrating capabilities across NLP, computer vision, and machine learning to build robust multi-modal AI solutions Interact with clients and other team members to understand client-specific requirements of the platform Contribute to platform development team and deliver platform releases in a timely manner • Liaise with multiple stakeholders and coordinate with our onshore and offshore entities • Evaluate and compile the required training datasets from internal and public sources and contribute to the data pre-processing phase. Expected and Desired Skills Either of the following Deep learning frameworks – PyTorch (preferred) or Tensorflow • Good understanding in designing, developing, and optimizing Large Language Models (LLMs), with hands-on experience in leveraging cutting-edge advancements in NLP and generative AI Skilled in customizing LLMs for domain-specific applications through advanced fine-tuning, prompt engineering, and optimization strategies such as LoRA, quantization, and distillation. • Knowledge of model versioning, serving, and monitoring using tools like MLflow, FastAPI, Docker, vLLM. Python used for analytics applications including data pre-processing, EDA, statistical analysis, machine learning model performance evaluation and benchmarking Good scripting and programming skills to integrate with other external applications • Good interpersonal skills and the ability to communicate and explain models • Ability to work in unfamiliar business areas and to use your skills to create solutions • Ability to both work in and lead a team and to deliver and accept peer review • Flexible approach to working environment and hours. Experience Between 4-6 years of relevant experience Hands-on experience with o Python and/or R o Machine Learning o Deep Learning (desirable) End to End development of a Deep Learning based model covering model selection, data preparation, training, hyper-parameter optimization, evaluation, and performance reporting. Proven experience working in both smaller and larger organisations having multicultural exposure Domain and industry experience by serving customers in one or more of these industries - Financial Services, Professional Services, other Consumer Industries Education Background: A Bachelor’s degree in the fields of study such as Computer Science, Mathematics, Statistics, and Data Science with strong programming content from a leading institute An advanced degree such as a Master's or PhD is an advantage Job Type: Full-time Pay: ₹1,000,000.00 - ₹2,000,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

Job Requirements Key Responsibilities Design and Development: Design and implement AI/ML-based applications tailored for embedded and edge hardware. Develop end-to-end pipelines for model training, conversion, and deployment. Customize neural network architectures for edge-specific applications such as object detection, classification, and segmentation. Model Optimization and Deployment: Port and optimize AI models to meet performance and memory constraints on edge platforms. Apply quantization (e.g., INT8), pruning, and layer fusion techniques to improve model efficiency. Convert models between various formats such as ONNX, TensorRT, TVM, TFLite, and DRP-AI. Performance Tuning and Profiling: Analyze model bottlenecks and tune for latency, throughput, and power efficiency. Run inference performance profiling on hardware targets and iterate for improvements. Testing and Debugging: Validate model accuracy and performance post-optimization. Debug and troubleshoot model behavior discrepancies across frameworks and devices. Documentation and Research: Maintain documentation for all model lifecycle stages and optimization steps. Stay updated with latest AI compiler advancements and deployment trends in edge AI. Work Experience Must Have : Bachelor's/Master’s degree in Computer Science, Electronics, or AI-related field. 6+ years in AI/ML model development with experience in real-world applications. Proficient in Python, C++ and deep learning libraries (TensorFlow, PyTorch, Keras). Solid understanding of CNNs, FCNs, and their applications in computer vision. Practical knowledge of model optimization workflows (quantization, pruning, etc.). Experience with ONNX, TVM, TensorRT, DRP-AI, TFLite, OpenCV, etc. Experience with deployment on edge devices like Jetson, RZ/V2H, or STM32. Strong understanding of constraints (compute, memory, power) in edge environments. Good to Have: Exposure to embedded Linux or RTOS environments. Familiarity with low-level model debugging, calibration tools, and inference engines. Experience with Continuous Integration tools such as Git, Jenkins, or similar. Understanding of hardware accelerators (GPU, NPU, DRP-AI, etc.).

Required Skills We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a strong background in designing, deploying, and maintaining advanced AI/ML models with expertise in Natural Language Processing (NLP), Computer Vision, and architectures like Transformers and Diffusion Models. You will play a key role in developing AI-powered solutions, optimizing performance, and deploying and managing models in production environments. Key Responsibilities 1. AI Model Development and Optimization: Design, train, and fine-tune AI models for NLP, Computer Vision, and other domains using frameworks like TensorFlow and PyTorch. Work on advanced architectures, including Transformer-based models (e.g., BERT, GPT, T5) for NLP tasks and CNN-based models (e.g., YOLO, VGG, ResNet) for Computer Vision applications. Utilize techniques like PEFT (Parameter-Efficient Fine-Tuning) and SFT (Supervised Fine-Tuning) to optimize models for specific tasks. Build and train RLHF (Reinforcement Learning with Human Feedback) and RL-based models to align AI behavior with real-world objectives., Explore multimodal AI solutions combining text, vision, and audio using generative deep learning architectures. 2. Natural Language Processing (NLP): Develop and deploy NLP solutions, including language models, text generation, sentiment analysis, and text-to-speech systems. Leverage advanced Transformer architectures (e.g., BERT, GPT, T5) for NLP tasks. 3. AI Model Deployment and Frameworks: Deploy AI models using frameworks like VLLM, Docker, and MLFlow in production-grade environments. Create robust data pipelines for training, testing, and inference workflows. Implement CI/CD pipelines for seamless integration and deployment of AI solutions. 4. Production Environment Management: Deploy, monitor, and manage AI models in production, ensuring performance, reliability, and scalability. Set up monitoring systems using Prometheus to track metrics like latency, throughput, and model drift. 5. Data Engineering and Pipelines: Design and implement efficient data pipelines for preprocessing, cleaning, and transformation of large datasets. Integrate with cloud-based data storage and retrieval systems for seamless AI workflows. 6. Performance Monitoring and Optimization: Optimize AI model performance through hyperparameter tuning and algorithmic improvements. Monitor performance using tools like Prometheus, tracking key metrics (e.g., latency, accuracy, model drift, error rates etc.) 7. Solution Design and Architecture: Collaborate with cross-functional teams to understand business requirements and translate them into scalable, efficient AI/ML solutions. Design end-to-end AI systems, including data pipelines, model training workflows, and deployment architectures, ensuring alignment with business objectives and technical constraints. Conduct feasibility studies and proof-of-concepts (PoCs) for emerging technologies to evaluate their applicability to specific use cases. 8. Stakeholder Engagement: Act as the technical point of contact for AI/ML projects, managing expectations and aligning deliverables with timelines. Participate in workshops, demos, and client discussions to showcase AI capabilities and align solutions with client needs. Technical Skills Proficient in Python , with strong knowledge of libraries like NumPy, Pandas, SciPy, and Matplotlib for data manipulation and visualization. Expertise in TensorFlow, PyTorch, Scikit-learn, and Keras for building, training, and optimizing machine learning and deep learning models. Hands-on experience with Transformer libraries like Hugging Face Transformers, OpenAI APIs, and LangChain for NLP tasks. Practical knowledge of CNN architectures (e.g., YOLO, ResNet, VGG) and Vision Transformers (ViT) for Computer Vision applications. Proficiency in developing and deploying Diffusion Models like Stable Diffusion, SDX, and other generative AI frameworks. Experience with RLHF (Reinforcement Learning with Human Feedback) and reinforcement learning algorithms for optimizing AI behaviors. Proficiency with Docker and Kubernetes for containerization and orchestration of AI workflows. Hands-on experience with MLOps tools such as MLFlow for model tracking and CI/CD integration in AI pipelines. Expertise in setting up monitoring tools like Prometheus and Grafana to track model performance, latency, throughput, and drift. Knowledge of performance optimization techniques, such as quantization, pruning, and knowledge distillation, to improve model efficiency. Experience in building data pipelines for preprocessing, cleaning, and transforming large datasets using tools like Apache Airflow, Luigi Familiarity with cloud-based storage systems (e.g., AWS S3, Google BigQuery) for efficient data handling in AI workflows. Strong understanding of cloud platforms (AWS, GCP, Azure) for deploying and scaling AI solutions. Knowledge of advanced search technologies such as Elasticsearch for indexing and querying large datasets. Familiarity with edge deployment frameworks and optimization for resource-constrained environments Qualifications · Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. Experience: 2.5 to 5 yrs Location: Trivandrum Job Type: Full-time Pay: ₹500,000.00 - ₹1,100,000.00 per year Benefits: Health insurance Provident Fund Location Type: In-person Schedule: Day shift Work Location: In person

Why join Stryker? Looking for a place that values your unique talents? Discover Stryker's award-winning culture. We are proud to offer you our total rewards package which includes bonuses, healthcare, insurance benefits, retirement programs, wellness programs, as well as service and performance awards – not to mention various social and recreational activities, all of which are location specific. Job description We are excited to be named one of the World’s Best Workplaces by Fortune Magazine! We are proud to offer you our total rewards package which includes bonuses, healthcare, insurance benefits, retirement programs, wellness programs, as well as service and performance awards – not to mention various social and recreational activities, all of which are location specific. Who we want: Experienced and motivated professional who is talented to lead on the technical front, take challenges and work with globally distributed teams to develop state of the art computer vision solutions for medical products. What you will do: Requirement gathering, Designing, Implementation and Documentation Leverage new technologies to excel product offering and performance Work with all the stakeholders to ensure timely deliveries of the tasks Compliance to Quality Management System and Design Controls Preferred Qualifications (Strongly desired): Essential 6 to 8 years of research experience in developing best in class computer vision and/or video analytics solutions Broad understanding of state-of-art deep learning architectures for computer vision tasks (segmentation/object detection/tracking/3D Vision/VSLAM) Proficiency in Python programming. Strong expertise in PyTorch – Core/Tools Experience with model optimization (quantization/distillation/pruning) Experience in debugging Numpy+PyTorch model export to ONNX/TRT format Excellent written and oral English communication skills Experience in working with distributed teams across geographies in agile setup Self-learner and the ability to work hands-on with minimal supervision or assistance Good to Have Track record of innovation in deep-learning (open-source projects and/or publications) Experience in C++ development, Visual Studio and Linux/Windows build systems Experience working in healthcare industry on Medical Imaging Education: Bachelors or Master degree in computer science, computer engineering or a related science or engineering discipline is required. A relevant PhD or equivalent experience would be favored. Experience: 4 -8 years Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 150 million patients annually.

Data Scientist – Deep Learning (Financial Services Domain) We are seeking a highly skilled and motivated Data Scientist with a strong background in deep learning and quantitative analysis to join our advanced AI team. This role is ideal for professionals who are passionate about applying cutting-edge machine learning techniques to solve complex problems in the financial services domain. Key Responsibilities: Design, implement, and deploy deep learning models for financial use cases, including stock price prediction, risk scoring, and algorithmic trading. Optimize models for performance and scalability through techniques such as quantization, pruning, and efficient architecture design. Rigorously evaluate models using appropriate metrics, validation techniques, and hyperparameter tuning, while maintaining robust experiment tracking practices. Deploy and maintain machine learning workflows using MLOps best practices on cloud platforms (AWS preferred). Conduct exploratory data analysis (EDA), feature engineering, and time-series analysis on structured and unstructured financial datasets. Apply advanced pattern recognition techniques to derive insights and predictive signals from data. Stay abreast of the latest research in deep learning, including advancements in LLMs, attention mechanisms, and financial NLP. Collaborate with cross-functional teams, including quantitative analysts, fellow data scientists, and product managers, to translate business requirements into technical solutions. Ensure high-quality code, documentation, and backtesting processes. Required Qualifications: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related discipline from a reputed institute (IITs or BITS preferred). 5-7 years of experience in developing and deploying deep learning or AI models, ideally within the financial services industry. Hands-on experience with PyTorch or TensorFlow , and Python data libraries such as pandas, NumPy, and scikit-learn . Strong background in predictive modeling, anomaly detection, and pattern recognition using financial data. Proficient in Python or PySpark for large-scale data processing. Ability to work with diverse financial datasets, including stock prices, order books, financial statements, and alternative data sources. Preferred Qualifications: Experience with cloud platforms (AWS, GCP, or Azure) for model training, deployment, and scaling. Familiarity with ML pipelines, Docker, and modern MLOps frameworks. Exposure to Natural Language Processing in finance (e.g., sentiment analysis, earnings call transcripts). Working knowledge of core financial concepts such as P&L, return metrics, technical indicators, and risk measurement.