12 Model Quantization Jobs

As an experienced AI Architect, your role will involve leading the design, development, and deployment of large-scale AI solutions. You will be responsible for bridging the gap between business requirements and technical implementation, with a focus on generative AI and modern MLOps practices. Key Responsibilities: - Architect end-to-end AI systems utilizing large language models and generative AI technologies - Design scalable, production-ready AI applications that align with business objectives and performance requirements - Evaluate and integrate LLM APIs from leading providers such as OpenAI, Anthropic Claude, and Google Gemini - Establish best practices for prompt engineering, model selection, and AI system optimization - Fine-tune open-source models like Llama and Mistral for specific business use cases - Implement custom training pipelines and evaluation frameworks - Optimize model performance, latency, and cost for production environments - Stay updated with the latest model architectures and fine-tuning techniques - Deploy and manage AI models at an enterprise scale using containerization (Docker) and orchestration (Kubernetes) - Build robust, scalable APIs using FastAPI and similar frameworks - Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment - Ensure high availability, security, and performance of AI systems in production - Collaborate with stakeholders to understand business problems and translate them into technical requirements - Provide technical guidance and mentorship to development teams - Conduct feasibility assessments and technical due diligence for AI initiatives - Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: - 7+ years of experience in machine learning engineering or data science - Proven track record of delivering large-scale ML solutions Technical Skills: - Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) - Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) - Strong proficiency in FastAPI, Docker, and Kubernetes - Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) - Proficiency in Python and modern software development practices - Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: - Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques - Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) - Ability to translate complex business requirements into technical solutions - Strong problem-solving skills and architectural thinking Preferred Qualifications: - Experience with vector databases and retrieval-augmented generation (RAG) systems - Knowledge of distributed training and model parallelization techniques - Experience with model quantization and optimization for edge deployment - Familiarity with AI safety, alignment, and responsible AI practices - Experience in specific domains (finance, healthcare, legal, etc.) - Advanced degree in Computer Science, AI/ML, or related field,

Qualcomm is a company at the forefront of innovation, unlocking AI on Edge and accelerating connectivity to transform industries and enrich lives. As part of the Multimedia Audio Systems Group, you will have the opportunity to work on Voice AI models such as ASR, TTS, NLP, Multilingual Translation, and more. Your role will involve prototyping, productizing, and optimizing Voice AI models for efficient offload to NPU, GPU, and CPU. Additionally, you will collaborate with R&D and Systems teams for system integration, use case validation, and commercialization support. **Key Responsibilities:** - Prototype and productize Voice AI Models including ASR, TTS, NLP, Multilingual Translation, Summarization, Language modeling, etc. - Develop, Train, and Optimize Voice AI models for efficient offload to NPU, GPU, and CPU. - Conduct Model evaluation study and Competitive analysis with multiple open source model variants, and work on different model architectures. - Collaborate with R&D and Systems team for system integration, use case validation, efficient offload to HW accelerators, and commercialization support. **Qualifications Required:** - Strong programming skills in C/C++, Python - Experience in ML inference optimizations - Proficiency in designing, implementing, and training DL models in high-level languages/frameworks (e.g. PyTorch, TensorFlow, ONNX) - Knowledge of ML architectures and operators like Transformers, LSTM, GRUs - Familiarity with recent trends in machine learning and traditional statistical modeling/feature extraction techniques - Experience in Speech-to-text, Text-to-Speech, Speech-to-Speech, NLP applications - Knowledge of Model quantization and compression techniques - Expertise in developing and debugging software on embedded platforms - Knowledge of software design patterns, multi-threaded programming, computer architecture, operating systems, data structures, and algorithms - Familiarity with fixed-point coding - Experience with AI HW accelerators NPU or GPU is a plus Qualcomm values diversity and encourages individuals with disabilities to apply. Reasonable accommodations can be provided during the application/hiring process. If you meet the educational qualifications and have 2+ years of relevant work experience, you are encouraged to apply for this exciting opportunity in Voice AI modeling at Qualcomm.,

The Jr. AI Engineer position based in Bengaluru, Karnataka requires 1-2 years of experience and is a Work From Office (WFO) role. As a member of the expanding AI team, you will be involved in developing LLM-driven products from scratch. Your primary responsibilities will include designing state-of-the-art systems and implementing AI solutions that have a global impact. To excel in this role, you need to possess strong communication skills and problem-solving abilities. A solid programming background is essential, as well as a deep understanding of Transformer architecture. The ideal candidate should have 1-2 years of hands-on experience in AI/ML, specifically working on projects involving Transformers such as BERT, GPT, T5, ViTs, and Small LLMs. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is a must. Moreover, you should be capable of independently analyzing open sources and code repositories. Experience in fine-tuning Transformer models for Natural Language Processing (NLP) tasks like text classification and summarization, or Computer Vision tasks such as image generation and recognition, is highly desirable. Knowledge of GPU acceleration, optimization techniques, and model quantization is expected. Additionally, experience in deploying models using Flask, FastAPI, or cloud-based inference services is advantageous. Familiarity with data pre-processing, feature engineering, and training workflows will be beneficial in this role. It is important to note that candidates who have only completed online courses or certifications without real-world projects, have less than 6 months of applied experience in Transformer models, or have no experience in deploying models beyond Jupyter Notebooks will not be considered for this position.,

NewCold is a service provider in cold chain logistics with a focus on the development and operation of large, highly automated cold stores. We strive to play a crucial role in the cold chain of leading food companies by offering advanced logistic services worldwide. As one of the fastest-growing companies in the cold chain logistics industry, with over 2,000 employees, we are expanding our teams to support this growth. We utilize the latest technology to empower individuals to handle food responsibly and ensure food safety in a sustainable manner. Challenging the industry norms, we believe in forming long-term partnerships and delivering solid investment opportunities that pave the way for next-generation logistic solutions. With in-house expertise in designing, engineering, developing, and operating state-of-the-art automated cold stores, we have successfully executed projects across three continents. As we anticipate numerous new construction projects globally in the near future, this vacancy presents an exciting opportunity to be part of an internationally growing and ambitious organization. **Job Title:** AI Associate-Computer Vision **Location:** Bengaluru **Experience:** 1-2 Years **Compensation:** Up to 15 Lakhs PA **Position:** AI Associate - Computer Vision We are seeking a passionate and hands-on AI Associate (Computer Vision) to join our AI team. In this role, you will work on real-world applications using live video feeds and image data to develop intelligent visual systems that address significant challenges across logistics, operations, and automation. **Your Role:** This position offers an excellent opportunity for individuals looking to enhance their expertise in computer vision while contributing to the development of production-grade systems with tangible business impacts. **What You'll Do:** - Develop and train computer vision models for tasks such as object detection, tracking, OCR, and image classification. - Utilize tools like YOLO, OpenCV, and Detectron2 to address visual automation challenges. - Integrate vision models with real-time video streams (RTSP) or batch-based pipelines. - Prepare and annotate image/video datasets using modern data labeling tools. - Collaborate closely with data engineers and software developers to deploy models at scale using APIs or edge systems. - Monitor and fine-tune model performance based on live deployment feedback. - Document training approaches, data pipeline steps, and model behavior to facilitate continuous improvement. **What We're Looking For:** - B.Tech / M.Tech in Computer Science, Electrical Engineering, or a related field. - 1-2 years of experience in building computer vision solutions. - Strong Python skills and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow). - Familiarity with image/video preprocessing, model evaluation, and optimization techniques. - Experience working with live video feeds or edge inference pipelines is advantageous. - Knowledge of version control (Git) and exposure to deploying models on cloud platforms (Azure preferred). **Nice to Have:** - Experience with ONNX, model quantization, or edge deployment tools. - Exposure to CV data labeling platforms like CVAT, Label Studio, or SuperAnnotate. - Understanding of MLOps practices for model packaging, versioning, and monitoring.,

We are looking for a talented individual who has recently completed their PhD to join our cutting-edge team. This position is specifically tailored for fresh PhD graduates who are eager to apply their research expertise in a dynamic industry setting. In this role, you will be tasked with tackling complex challenges in large language models (LLMs), optical character recognition (OCR), and model scaling. You will have the opportunity to be at the forefront of developing and optimizing AI systems that push the boundaries of what's possible in machine learning. As part of your responsibilities, you will lead research initiatives aimed at enhancing OCR accuracy across diverse document types and languages. You will also work on training and fine-tuning LLMs using domain-specific data to improve performance in specialized contexts. Additionally, you will be involved in developing techniques to efficiently scale LLMs for high-volume production environments, as well as designing and implementing novel approaches to model optimization and evaluation. Collaboration with cross-functional teams to integrate AI solutions into production systems will be a key aspect of this role. It is important to stay current with the latest research and incorporate state-of-the-art techniques into your work. Documenting methodologies, experiments, and findings for both technical and non-technical audiences will also be part of your responsibilities. To qualify for this role, you must have a PhD in Computer Science, Machine Learning, AI, or a related field completed within the last year. A strong understanding of deep learning architectures, particularly transformer-based models, is required. Experience with OCR systems and techniques for improving text recognition accuracy is essential. Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX is a must. Demonstrated ability to implement and adapt research papers into working code, excellent problem-solving skills, and strong communication skills are also necessary. Preferred qualifications include a research focus during your PhD in areas relevant to our work (NLP, computer vision, multimodal learning), familiarity with distributed training systems for large-scale models, experience with model quantization, pruning, and other efficiency techniques, understanding of evaluation methodologies for assessing model performance, knowledge of MLOps practices and tools for model deployment, and publications at top-tier ML conferences (NeurIPS, ICML, ACL, CVPR, etc.). In return, we offer an ideal transition from academic research to industry application, a structured onboarding program designed specifically for recent PhD graduates, the opportunity to work on frontier AI models with real-world impact, access to significant computing resources for ambitious research, a collaborative environment with other top AI researchers and engineers, flexible work arrangements, competitive compensation, support for continued professional development and conference attendance, and a clear path for growth into senior technical or leadership roles. FourKites is the leader in AI-driven supply chain transformation for global enterprises, pioneering real-time visibility and turning supply chain data into automated action. Our Intelligent Control Tower breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory, and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across the supply chain. In addition to the exciting work environment, we offer medical benefits starting on the first day of employment, 36 PTO days (sick, casual, and earned), 5 recharge days, 2 volunteer days, home office setups, and technology reimbursement, lifestyle and family benefits, annual swags/festive swags, ongoing learning and development opportunities (professional development program, Toast Master club, etc.).,

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ AI/ML Development Engineer Job Description: We are seeking a highly skilled AI/ML Development Engineer with deep expertise in cutting-edge AI and machine learning algorithms and inference workloads. The ideal candidate will have comprehensive experience across key embedded domains including computer vision, voice recognition, and generative AI leveraging large language models (LLMs). Key Responsibilities: Design, develop, and optimize AI/ML models and inference pipelines tailored for embedded systems. Implement and integrate AI/ML model operators and kernels on popular hardware accelerators such as GPUs and NPUs. Perform model quantization and apply other efficient inference techniques to maximize performance and resource utilization on embedded platforms. Deliver end-to-end AI solutions including deployment, performance profiling, and debugging for customer-specific applications. Collaborate closely with cross-functional teams to resolve technical issues and optimize AI workloads in real-time embedded environments. Develop and maintain software primarily on Linux platforms, utilizing standard AI frameworks such as ONNX Runtime and AMD ROCm. Qualifications: In-depth knowledge of state-of-the-art AI/ML algorithms and inference workloads, with a strong focus on embedded applications. Proven experience with AI/ML model operators and kernel development on hardware accelerators including GPUs and NPUs. Hands-on expertise in model quantization and efficient inference methods for resource-constrained embedded systems. Solid experience with Linux-based software development, real-time embedded systems, and AI frameworks like ONNX Runtime and AMD ROCm. Strong problem-solving skills and ability to troubleshoot and resolve customer-specific AI/ML deployment issues. Preferred: Experience with computer vision, voice recognition, and generative AI (LLMs) applications. Familiarity with performance profiling and optimization tools for embedded AI workloads ACADEMIC CREDENTIALS: Bachelor's or Master's degr ee in Computer or Electrical Engineering or equivalent #LI-MK1 Benefits offered are described: . AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants needs under the respective laws throughout all stages of the recruitment and selection process.

You should have a minimum of 2 years of relevant experience in Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. Additionally, you should have exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. Moreover, hands-on experience with modality-specific encoder models for multi-modal AI applications and proficiency in model fine-tuning, prompt engineering, and using both open-source and proprietary LLMs is required. Experience with model quantization, optimization, and conversion techniques for efficient deployment, including edge devices is also essential. You should possess a deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. Strong MLOps knowledge is required with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions is a must. Familiarity with data preprocessing, standardization, and knowledge graphs is considered a nice-to-have skill. Furthermore, you should have a strong analytical mindset with a passion for building robust, scalable AI solutions and be skilled in Python, writing clean, modular, and efficient code. Proficiency in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic is also required. Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search is essential. Exposure to Neo4j and graph databases for relationship-driven insights is a plus. Hands-on experience with Docker and containerization to build scalable, reproducible, and portable AI services is expected. Being up-to-date with the latest trends in GenAI, LLMs, Agentic AI, and deployment strategies is crucial. Strong communication and collaboration skills are necessary, as you should be able to contribute in cross-functional and fast-paced environments. Bonus skills include experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing, as well as working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar technologies. This is a full-time job with a day shift schedule. The expected start date is 23/06/2025. The work location is in person.,

Are you ready to experiment, learn, and implement in the field of ML, Python, Computer Vision, hardware platforms like Jetson Nano and Raspberry Pi, and cloud services Join us on a new adventure where your expertise can revolutionize the dynamics of our organization. We believe in selection, not rejection, and we are excited to welcome you to our team. OptiSol is your destination for a stress-free and balanced lifestyle. We provide a nurturing environment where your career can flourish. As a certified GREAT PLACE TO WORK for 4 consecutive years, we value open communication, accessible leadership, diversity, and work-life balance with flexible policies. At OptiSol, you can thrive both personally and professionally. We are at the forefront of AI and innovation, shaping the future together. Join us on this journey of learning and growth. What we like to see in you: - Core Competencies: Programming, AI Expertise, IoT Hardware, Protocols (RTSP, TCP, MQTT, Modbus, UART), Leadership - Bachelor's/masters in computer science, ECE, or related fields - Expertise in Python and relevant ML frameworks (TensorFlow, PyTorch, OpenCV) - Strong understanding of neural networks, transfer learning, and optimization techniques - Proficiency with Jetson Nano, Raspberry Pi, Arduino, and related platforms - Familiarity with RTSP, TCP, MQTT, Modbus, UART - Proven experience in leading technical teams and managing projects What do we expect: - Hands-on experience with model quantization, multitask learning, and zero-shot fine-tuning - Familiarity with OCR and multimodal LLMs for different data types - Experience in API development using FastAPI and Django, plus Android AI apps - Knowledge of industrial cameras, motor drivers, and Ethernet switches - Proficiency in CUDA programming and GPU optimization What You'll Bring to the Table: - Lead a team of AI engineers and promote a creative and collaborative environment - Work with stakeholders to define project goals and milestones - Deliver high-quality AI-driven solutions on time - Tweak machine learning and computer vision algorithms for tasks like object detection - Deploy AI on edge devices like Jetson Nano or Raspberry Pi - Integrate AI models with electronics and solve hardware-software challenges - Manage AI services on cloud platforms (AWS, Azure, Google Cloud) - Test, validate, and document solutions following industry best practices Core benefits you'll gain: - Lead and inspire a team of engineers in a collaborative setting - Directly shape project goals and ensure project success - Gain hands-on experience in cutting-edge AI and computer vision applications - Dive into edge devices like Jetson Nano and Raspberry Pi - Manage AI services on cloud platforms securely and efficiently - Develop a well-rounded skill set in AI and hardware Join us as an OptiSolite and discover a fulfilling career with us. Explore life at OptiSol and learn more about our culture on our Insta Page.,

Qualcomm India Private Limited is seeking a candidate to join their Multimedia Audio Systems Group as a Voice AI Engineer. As part of the team, you will be responsible for prototyping and productizing Voice AI Models for tasks such as Automatic Speech Recognition (ASR), Text-to-Speech (TTS), NLP, Multilingual Translation, Summarization, Language modeling, and other Speech/text generation tasks. You will work closely with a team of engineers to develop, train, and optimize Voice AI models for efficient offload to NPU, GPU, and CPU. Additionally, you will conduct model evaluation studies, competitive analysis, and collaborate with other R&D and Systems teams for system integration, use case validation, efficient offload to HW accelerators, and commercialization support. The ideal candidate should have strong programming skills in C/C++ and Python, along with experience in ML inference optimizations. Proficiency in designing, implementing, and training DL models using high-level languages/frameworks such as PyTorch, TensorFlow, and ONNX is required. Knowledge of ML architectures and operators like Transformers, LSTM, GRUs, and familiarity with recent trends in machine learning and traditional statistical modeling/feature extraction techniques are essential. Experience in Speech-to-text, Text-to-Speech, Speech-to-Speech, NLP applications, model quantization, compression techniques, software development on embedded platforms, software design patterns, multi-threaded programming, computer architecture, operating systems, data structures, algorithms, fixed-point coding, and AI HW accelerators (NPU or GPU) is a plus. Candidates should hold a Bachelor's/Masters/PhD degree in Engineering, Electronics and Communication, Computer Science, or related field, along with 3+ years of experience in Audio Systems engineering, Audio Signal Processing modules, ML Model development, or related work. Minimum qualifications include a Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 2+ years of Systems Engineering or related work experience, or a Master's degree with 1+ year of experience, or a PhD in a related field. Qualcomm is an equal opportunity employer committed to providing accessible processes for individuals with disabilities. Individuals seeking accommodation during the application/hiring process can contact Qualcomm for support. The company expects its employees to adhere to all applicable policies and procedures, including security requirements regarding protection of confidential information. Please note that Qualcomm does not accept unsolicited resumes or applications from agencies. Staffing and recruiting agencies are not authorized to submit profiles, applications, or resumes on behalf of individuals. For more information about this role, please contact Qualcomm Careers.,

THE ROLE: AMD is looking for an influential software engineer who is passionate about improving the performance of key applications and benchmarks. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology. THE PERSON: The ideal candidate shall have in-depth knowledge on state-of-the-art AI/ML algorithms and inference workloads spanning across key embedded domains such as computer vision, voice recognition, and generative AI using LLMs. In addition, prior experience in AI/ML model operators and kernels on popular HW accelerators including GPUs and NPUs are highly desirable. The ability to perform model quantization and other efficient inference techniques for embedded systems are essential. As an AI/ML development engineer, you will be tasked with various implementations ranging from end-to-end AI pipeline delivery, performance profiling, to customer-specific issue resolutions. We emphasize Linux-based software development with real-time embedded applications, and also standard frameworks such as ONNX RT and AMD ROCm. ACADEMIC CREDENTIALS: Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

Arivon is seeking an Artificial Intelligence (AI) Software Engineer with expertise in generative AI, Natural Language Processing (NLP), and LLM. The ideal candidate should have a minimum of 5 years of experience in NLP and Generative AI and LLM research. The role involves tasks such as language model evaluation, data processing for pre-training and fine-tuning, LLM alignment, reinforcement learning for language model tuning, and efficient training and inference. Additionally, the candidate should have experience in multilingual and multimodal modeling. The AI Software Engineer should have hands-on experience with Machine Learning (ML), NLP, and Deep Learning (DL) frameworks like PyTorch, Tensorflow, and SFT on LLM. Proficiency in leveraging LangChain for the development and integration of LLMs into various applications is essential. The candidate should demonstrate a strong ability to enhance AI functionalities through innovative applications of natural language processing and understanding. Experience with model quantization or computational optimizations is considered a plus. Familiarity with cloud platforms such as AWS, GCP, and Azure is advantageous, and prior experience in the Healthcare domain is a bonus. The role also involves designing methods, tools, and infrastructure to advance the state of the art in large language models. Responsibilities include deploying, monitoring, and managing ML models in production to ensure high availability and low latency. The candidate will be expected to manage and optimize ML infrastructure, including cloud services, containers, and orchestration tools. A Master's degree in computer science, computer engineering, or a related technical field is required, while a Ph.D. in AI, computer science, data science, or related fields is preferred. Proficiency in programming languages like Python is necessary for this role.,

Key Responsibilities: Responsibilities Anchor ML development track in a client project Data collection profiling EDA data preparation AI Model development experimentation tuning validation Present findings to business users project management teams Propose ML based solution approaches estimates for new use cases Contribute to AI based modules in Infosys solutions development Explore new advances in AI continuously and execute PoCs Mentoring Guide junior team members evangelize AI in organization Technical skills Programming Python R SQL ML algorithms o Statistical ML algorithms o Deep Neural Network architectures o Model ensembling o Generative AI models o ML for Responsible AI AI domains NLP speech computer vision structured data Learning patterns supervised unsupervised reinforcement learning Tools for data analysis auto ML model deployment scaling model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets pre built models available in open community and 3rd party providers Knowledge of software development architectures Knowledge of hyperscalers their AI capabilities Azure AWS GCP Knowledge of Model Quantization and Pruning Preferred Skills: Technology->Machine learning->data science,Technology->Data Science->Machine Learning,Technology->Machine Learning->Accord,Technology->Machine Learning->Generative AI