8 Model Compression Jobs

Hello Talented Techie! To solve the biggest challenges of our time, we need inquisitive minds with the ambition to make the impossible possible. Siemens is your place to thrive, challenge the status quo, make a difference, and grow in a team of innovators who share your passion for tech. Are you in We are looking for a Research Engineer Introduction With over 1,900 research operatives worldwide, the Technology organization occupies a special position within Siemens R&D facilities. It functions as an international network of expertise and as a global partner for technology and innovations. Through its R&D activities in Germany, the USA, China, India, Russia and Eastern Europe, Technology helps secure the company's technological future and bolster its competitiveness. You'll create impact by: PhD/master's degree in computer science and from a reputed institute with grass-root experience of at least 3+ years in designing & solving complex problems and deriving actionable insights. Hands-on experience with one or more of the following is a must: Solid hands-on experience in training deep convolutional and/or recurrent networks using frameworks like Tensorflow, Caffe and PyTorch Hands-on experience using OpenCV and OpenGL Research, develop and prototype software related to object detection, tracking, semantic segmentation, action recognition, 3D reconstruction, SLAM Hands-on experience dealing with multimodal data (audio, video, text, sensors, etc.,) and suggest cases with the best technology option for prototyping and productization. Optimization techniques and model compression for deployment on resource-constrained hardware/edge devices Image processing, Computer vision and Video Analytics problems with a clear understanding and ability to implement algorithms (especially deep learning algorithms) Experience building AI powered solutions for embedded platforms & compute constraint environments is a plus Knowledge of SaaS fundamentals is a plus Knowhow of solution design, architecture, software packaging using Docker/Kubernetes & deployment on cloud platforms is a plus Excited to collaborate with team members from idea generation, prototyping, present developed solutions and recommendations to business partners, and influence future technology roadmap and strategy of the portfolio. Have rich experience in understanding and influencing technology choices and building solutions to remove obstacles to adoption. Closely follow latest developments in artificial intelligence and be an early adopter of disruptive trends/technologies Extremely energetic and willing to walk the extra mile for achieving targets and be an active AI evangelist within and outside Siemens. Join Siemens: Create a better #TomorrowWithUs! We value your unique identity and perspective and are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society. Come bring your authentic self and create a better tomorrow with us. Protecting the environment, conserving our natural resources, encouraging the health and performance of our people as well as safeguarding their working conditions are core to our social and business dedication at Siemens.

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

As a part of Cowbell's innovative team in the field of cyber insurance, you will play a crucial role in designing and implementing RAG-based systems, integrating LLMs with vector databases, search pipelines, and knowledge retrieval frameworks. Your responsibilities will include developing intelligent AI agents that automate tasks, retrieve relevant information, and enhance user interactions. You will work with APIs, embeddings, and multi-modal retrieval techniques to improve the performance of AI applications. Additionally, you will be tasked with optimizing inference pipelines and enhancing LLM serving, fine-tuning, and distillation for efficiency. Staying abreast of the latest advancements in generative AI and retrieval techniques will be essential, along with collaborating with stakeholders and cross-functional teams to address business needs and develop impactful ML models and AI-driven automation solutions. The ideal candidate for this position should hold a Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field (or a Bachelor's degree with significant experience). You should have at least 5 years of experience in machine learning, deep learning, and NLP for real-world applications, as well as a minimum of 1 year of hands-on experience with LLMs and generative AI. Expertise in RAG architectures, vector search, and retrieval methods is required, along with proficiency in Python and experience with LLM APIs such as OpenAI, Hugging Face, Anthropic, etc. Experience in integrating LLMs into real-world applications, solid foundation in machine learning, statistical modeling, and AI-driven software development, as well as knowledge of prompt engineering, few-shot learning, and prompt chaining techniques are also preferred qualifications. Strong software engineering skills, including experience with cloud platforms like AWS, and excellent problem-solving abilities, communication skills, and the capacity to work independently are crucial for this role. Preferred qualifications for the position include proficiency in PyTorch or TensorFlow for deep learning model development, experience in LLM fine-tuning, model compression, and optimization, familiarity with frameworks like LangChain, LlamaIndex, or Ollama, experience with multi-modal retrieval systems (text, image, structured data), and contributions to open-source AI projects or published research in AI/ML. At Cowbell, employees are offered an equity plan, wealth enablement plan for select customer-facing roles, comprehensive wellness program, meditation app subscriptions, lunch and learn sessions, a book club, happy hours, and more for professional development and growth opportunities. The company is committed to fostering a collaborative and dynamic work environment where transparency and resilience are valued, and every employee is encouraged to contribute and thrive. Cowbell is an equal opportunity employer, promoting diversity and inclusivity in the workplace and providing competitive compensation, comprehensive benefits, and continuous opportunities for professional development. To learn more about Cowbell and its mission in the cyber insurance industry, please visit https://cowbell.insure/.,

Description By applying to this position, your application will be considered for all locations we hire for in the United States. Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time agoeven yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. Role AWS Neuron is the complete software stack for the AWS Trainium (Trn1/Trn2) and Inferentia (Inf1/Inf2) our cloud-scale Machine Learning accelerators. This role is for a Machine Learning Engineer on one of our AWS Neuron teams: The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances. Experience with training these large models using Python is a must. FSDP (Fully-Sharded Data Parallel), Deepspeed, Nemo and other distributed training libraries are central to this and extending all of this for the Neuron based system is key. ML?Frameworks partners with compiler, runtime, and research experts to make AWS?Trainium and?Inferentia feel native inside the tools builders already lovePyTorch, JAX, and the rapidly evolving vLLM ecosystem. By weaving Neuron?SDK deep into these frameworks, optimizing operators, and crafting targeted extensions, we unlock every teraflop of Annapurnas AI chips for both training and lightning?fast inference. Beyond kernels, we shape next?generation serving by upstreaming new features and driving scalable deployments with vLLM, Triton, and TensorRTturning breakthrough ideas into production?ready AI for millions of customers. The ML Inference team collaborates closely with hardware designers, software optimization experts, and systems engineers to develop and optimize high-performance inference solutions for Inferentia chips. Proficiency in deploying and optimizing ML models for inference using frameworks like TensorFlow, PyTorch, and ONNX is essential. The team focuses on techniques such as quantization, pruning, and model compression to enhance inference speed and efficiency. Adapting and extending popular inference libraries and tools for Neuron-based systems is a key aspect of their work. Key job responsibilities You&aposll join one of our core ML teams - Frameworks, Distributed Training, or Inference - to enhance machine learning capabilities on AWS&aposs specialized AI hardware. Your responsibilities will include improving PyTorch and JAX for distributed training on Trainium chips, optimizing ML models for efficient inference on Inferentia processors, and collaborating with compiler and runtime teams to maximize hardware performance. You&aposll also develop and integrate new features in ML frameworks to support AWS AI services. We seek candidates with strong programming skills, eagerness to learn complex systems, and basic ML knowledge. This role offers growth opportunities in ML infrastructure, bridging the gap between frameworks, distributed systems, and hardware acceleration. About The Team Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, Basic Qualifications To qualify, applicants should have earned (or will earn) a Bachelors or Masters degree between December 2022 and September 2025. Working knowledge of C++ and Python Experience with ML frameworks, particularly PyTorch, Jax, and/or vLLM Understanding of parallel computing concepts and CUDA programming Preferred Qualifications Experience in using analytical tools, such as Tableau, Qlikview, QuickSight Experience in building and driving adoption of new tools Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region youre applying in isnt listed, please contact your Recruiting Partner. Company - Annapurna Labs (U.S.) Inc. Job ID: A3029797 Show more Show less

If you are a smart, self-motivated Machine Learning Scientist with a passion for advancing the field of Generative AI, an excellent opportunity awaits you. EXL, a rapidly expanding global digital data-led AI transformation solutions company, is seeking candidates with deep expertise in developing and fine-tuning Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic solutions, and knowledge graph technologies to drive innovative solutions in Generative AI. You will have the chance to be at the forefront of pioneering advancements in AI, working alongside bright minds in an exciting R&D environment to build cutting-edge capabilities that redefine the future of artificial intelligence. In this role, you will develop initiatives in the Generative AI domain, focusing on cutting-edge technologies like LLMs, RAG, and autonomous agents. You will design and implement advanced workflows for integrating LLMs into real-world applications across domains such as Finance, Insurance, and Healthcare. Additionally, you will drive the development of retrieval-augmented systems by combining LLMs with document retrieval, clustering, and search techniques. Keeping abreast of AI advancements is essential, as you will be required to read, adapt, and implement cutting-edge research to solve real-world challenges. Documenting research findings, methodologies, and implementations for internal and external stakeholders will also be part of your responsibilities. Qualifications: - Experience: 2-5 years in AI/ML research and development, with at least 1-2 years focusing on Generative AI, LLMs, or related fields. - Education: Masters or PhD in Computer Science, AI, or a related field from a top-tier institution is highly preferred. Required Skills: - Core Expertise: Proven experience with Large Language Models (e.g., GPT-4, BERT, LLaMA, PaLM) and fine-tuning them for domain-specific applications. In-depth knowledge of Retrieval-Augmented Generation workflows and hands-on experience with autonomous agents. - Tools & Frameworks: Proficiency in deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Experience with distributed training and optimization on GPUs and TPUs. Familiarity with cloud ecosystems (AWS, Azure, Google Cloud) practices for scalable deployment. - Research & Development: Ability to read and adapt cutting-edge research papers for applied solutions in LLMs and knowledge graphs. Expertise in domain adaptation, few-shot learning, and zero-shot reasoning. Strong understanding of generative models and their integration with LLMs. - Problem Solving: Demonstrated ability to address challenges in unstructured data processing, including NLP and multimodal scenarios. Experience with document retrieval, clustering, and unsupervised learning techniques. Preferred Skills: - Experience with LLM fine-tuning and building Agentic systems for domain LLMs. Experience with reinforcement learning and fine-tuning via RLHF. Knowledge of large-scale optimization methods and efficient model compression techniques. Strong collaboration and communication skills, with a proven ability to lead teams. Experience with MoE based architecture and knowledge of federated learning.,

You will play a pivotal role in the design and implementation of cutting-edge GPU computers optimized for demanding deep learning, high-performance computing, and computationally intensive workloads. Your expertise will be essential in identifying architectural enhancements and innovative approaches to accelerate our deep learning models. Addressing strategic challenges related to compute, networking, and storage design for large-scale, high-performance workloads will be a key responsibility. Additionally, you will contribute to effective resource utilization in a heterogeneous computing environment, evolve our cloud strategy, perform capacity modeling, and plan for growth across our products and services. As an architect, you are tasked with translating business requirements pertaining to AI-ML algorithms into a comprehensive set of product objectives encompassing workload scenarios, end user expectations, compute infrastructure, and execution timelines. This translation should culminate in a plan to operationalize the algorithms efficiently. Furthermore, you will be responsible for benchmarking and optimizing Computer Vision Algorithms and Hardware Accelerators based on performance and quality KPIs. Your role will involve fine-tuning algorithms for optimal performance on GPU tensor cores and collaborating with cross-functional teams to streamline workflows spanning data curation, training, optimization, and deployment. Providing technical leadership and expertise for project deliverables is a core aspect of this position, along with leading, mentoring, and managing the technical team to ensure successful outcomes. Your contributions will be instrumental in driving innovation and achieving project milestones effectively. Key Qualifications: - Possess an MS or PhD in Computer Science, Electrical Engineering, or a related field. - Demonstrated expertise in deploying complex deep learning architectures. - Minimum of 5 years of relevant experience in areas such as Machine Learning (with a focus on Deep Neural Networks), DNN adaptation and training, code development for DNN training frameworks (e.g., Caffe, TensorFlow, Torch), numerical analysis, performance analysis, model compression, optimization, and computer architecture. - Strong proficiency in data structures, algorithms, and C/C++ programming. - Hands-on experience with PyTorch, TensorRT, CuDNN, GPU computing (CUDA, OpenCL, OpenACC), and HPC (MPI, OpenMP). - Thorough understanding of container technologies like Docker, Singularity, Shifter, Charliecloud. - Proficient in Python programming, bash scripting, and operating systems including Windows, Ubuntu, and Centos. - Excellent communication, collaboration, and problem-solving skills. Good To Have: - Practical experience with HPC cluster job schedulers such as Kubernetes, SLURM, LSF. - Familiarity with cloud computing architectures. - Hands-on exposure to Software Defined Networking and HPC cluster networking. - Working knowledge of cluster configuration management tools like Ansible, Puppet, Salt. - Understanding of fast, distributed storage systems and Linux file systems for HPC workloads. This role offers an exciting opportunity to contribute to cutting-edge technology solutions and make a significant impact in the field of deep learning and high-performance computing. If you are a self-motivated individual with a passion for innovation and a track record of delivering results, we encourage you to apply.,

The key responsibilities for this role include deploying and optimizing computer vision and deep learning models on Jetson family hardware platforms. You will be responsible for developing software to interface with sensors, cameras, and other peripherals to enable efficient data acquisition and processing. Additionally, you will implement and optimize algorithms for real-time applications, ensuring low latency and high performance. Collaborating with cross-functional teams to define system requirements and specifications will also be a part of your role. You will be expected to perform model compression, distillation, pruning, and quantization techniques to optimize model size and improve inference speed. Debugging and troubleshooting software and hardware issues on embedded systems is another key responsibility. Moreover, writing clean, efficient, and well-documented code is essential for this position. Please note that only candidates available for full-time (in-office) roles and able to start immediately are eligible to apply for this position. If you are passionate about pushing the boundaries of satellite-based insights and contributing to shaping the future of technology, we invite you to join our innovative team at SkyServe. Take this opportunity to be a part of Hyspace (SkyServe), a company that aims to remove barriers to accessing knowledge about Earth through autonomous technologies. Our vision is to create a global continual satellite sensing and computing platform by developing technologies and business models that integrate with the changing world. If you are ready to make an impact, we want to hear from you. Apply now and be a part of our exciting journey at SkyServe.,

Tata Electronics Pvt. Ltd. is a key global player in the electronics manufacturing industry, specializing in Electronics Manufacturing Services, Semiconductor Assembly & Test, Semiconductor Foundry, and Design Services. Established in 2020 by the Tata Group, the company's primary objective is to provide integrated solutions to global customers across the electronics and semiconductor value chain. We are looking for an AI Core Developer to join our R&D team in Bangalore. This role is centered around fundamental AI research, algorithm development, and model pre-training, focusing on innovation rather than application engineering. As an AI Core Developer, you will be involved in cutting-edge AI research, creating novel algorithms, and constructing foundation models from scratch. This position is ideal for individuals with a strong background in pre-training methodologies and algorithm development who aspire to contribute to core AI advancements. Your responsibilities will include developing and implementing innovative machine learning algorithms for various AI systems, designing pre-training pipelines for large models, prototyping new AI architectures, collaborating with research scientists and engineers, and contributing to technical publications. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, with 2-4 years of hands-on experience in AI/ML development. Proficiency in Python, C/C++, knowledge of deep learning frameworks such as PyTorch and TensorFlow, and experience with model pre-training are essential requirements. Strong mathematical skills, familiarity with transformer architectures and attention mechanisms, and understanding of distributed computing are also key competencies. Preferred qualifications include advanced experience in multimodal AI systems, research contributions to top-tier AI conferences, and expertise in specific AI domains like healthcare or finance. The position is based in Bangalore, India, with a hybrid work arrangement and occasional travel for conferences and collaborations.,