Location Multiple Locations

Description

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet). We recently demonstrated the feasibility of running a foundation model (Stable Diffusion) with >1 billion parameters on an Android phone under one second after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

• Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

• Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

• Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

• Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

• Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

• Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

• Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).

Canberra/Australia

We are looking for new outstanding PhD students for the upcoming scholarship round (application is due on 31st August 2024) at the Australian National University (ANU is ranked #30 in the QS Ranking 2025) or possibly at another Australian universities.

We are looking for new PhD students to work on new problems that may span over (but are not limited to) "clever" adapting of Foundation Models, LLMs, diffusion models (LORAs etc.,), NERF, or design of Graph Neural Networks, design of new (multi-modal) Self-supervised Learning and Contrastive Learning Models (masked models, images, videos, text, graphs, time series, sequences, etc. ) or adversarial and/or federated learning or other contemporary fundamental/applied problems (e.g., learning without backprop, adapting FMs to be less resource hungry, planning and reasoning, hyperbolic geometry, protein property prediction, structured output generative models, visual relation inference, incremental/learning to learn problems, low shot, etc.)

To succeed, you need an outstanding publication record, e.g., one or more first-author papers in venues such CVPR, ICCV, ECCV, AAAI, ICLR, NeurIPS, ICML, IJCAI, ACM KDD, ACCV, BMVC, ACM MM, IEEE. Trans. On Image Processing, CVIU, IEEE TPAMI, or similar (the list is non-exhaustive). Non-first author papers will also help if they are in the mix. Some patents and/or professional experience in Computer Vision, Machine Learning or AI are a bonus. You also need a good GPA to succeed.

We are open to discussing your interests and topics, if you reach out, we can discuss what is possible. Yes, we have GPUs.

If you are interested, reach out for an informal chat with Dr. Koniusz. I am at CVPR if you want to chat?): piotr.koniusz@data61.csiro.au (or piotr.koniusz@anu.edu.au, www.koniusz.com)

Location Bellevue, WA

Description Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale.

This role is for the AFT AI team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.

We are looking for an Applied Scientist with expertise in computer vision. You will work alongside other CV scientists, engineers, product managers and various stakeholders to deploy vision models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying computer vision for real world problems - this is the team for you.

Location Multiple Locations

Description The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. Qualcomm’s Cloud AI 100 accelerators are currently deployed at AWS / Cirrascale Cloud and at several large organizations. We are rapidly expanding our ML hardware and software solutions for large scale deployments and are hiring across many disciplines.

We are seeing to hire for multiple machine learning positions in the Qualcomm Cloud team. In this role, you will work with Qualcomm's partners to develop and deploy best in class ML applications (CV, NLP, GenAI, LLMs etc) based on popular frameworks such as PyTorch, TensorFlow and ONNX, that are optimized for Qualcomm's Cloud AI accelerators. The work will include model assessment of throughput, latency and accuracy, model profiling and optimization, end-to-end application pipeline development, integration with customer frameworks and libraries and responsibility for customer documentation, training, and demos. This candidate must possess excellent communication, leadership, interpersonal and organizational skills, and analytical skills.

This role will interact with individuals of all levels and requires an experienced, dedicated professional to effectively collaborate with internal and external stakeholders. The ideal candidate has either developed or deployed deep learning models on popular ML frameworks. If you have a strong appetite for technology and enjoy working in small, agile, empowered teams solving complex problems within a high energy, oftentimes chaotic environment then this is the role for you.

Minimum Qualifications: • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Applications Engineering, Software Development experience, or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Applications Engineering, Software Development experience, or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering, Software Development experience, or related work experience.

• 2+ years of experience with Programming Language such as C, C++, Java, Python, etc. • 1+ year of experience with debugging techniques.Key Responsibilities: Key contributor to Qualcomm’s Cloud AI GitHub repo and developer documentation. Work with developers in large organizations to Onboard them on Qualcomm’s Cloud AI ML stack improve and optimize their Deep Learning models on Qualcomm AI 100 deploy their applications at scale Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning. Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator. Optimize LLM/GenAI workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems. Partner with product management, hardware/software engineering to highlight customer progress, gaps in product features etc.

Location Sunnyvale, CA Bellevue, WA

Description Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique possibility to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. You will be part of a team committed to pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work on scale. This position requires experience with developing Multi-modal LLMs and Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.

Location Seattle, WA New York, NY

Description We are looking for an Applied Scientist to join our Seattle team. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. Our team solves a broad range of problems ranging from natural knowledge understanding of third-party shoppable content, product and content recommendation to social media influencers and their audiences, determining optimal compensation for creators, and mitigating fraud. We generate deep semantic understanding of the photos, and videos in shoppable content created by our creators for efficient processing and appropriate placements for the best customer experience. For example, you may lead the development of reinforcement learning models such as MAB to rank content/product to be shown to influencers. To achieve this, a deep understanding of the quality and relevance of content must be established through ML models that provide those contexts for ranking.

In order to be successful in our team, you need a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning. Our team utilizes a variety of AWS tools such as SageMaker, S3, and EC2 with a variety of skillset in shallow and deep learning ML models, particularly in NLP and CV. You will bring knowledge in many of these domains along with your own specialties.

Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As a Research Engineer for Optimization, you will focus on research and development related to the optimization of ML models on GPU’s or AI accelerators. You will use your judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems. Specifically, you will:

• Research, prototype and evaluate state of the art model optimization techniques and algorithms
• Characterize neural network quality and performance based on research, experiment and performance data and profiling
• Incorporate optimizations and model development best practices into existing ML development lifecycle and workflow.
• Define the technical vision and roadmap for DL model optimizations
• Write technical reports indicating qualitative and quantitative results to colleagues and customers
• Develop, deploy and optimize deep learning (DL) models on various GPU and AI accelerator chipsets/platforms

We are seeking a highly motivated candidate for a fully funded PhD position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain.

The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The PhD student is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV).

The start date of the position is September 01, 2024. The position is fully funded for 4 years by Science Foundation Ireland.

The successful candidate will require the following skills and knowledge: • Bachelor or Master in Computer Science or related fields; • Strong competence in computer graphics, computer vision; • Solid experience in academic research and publications is an advantage; • Additional background in math, statistics, or physics is an advantage. • Hands-on experience in training deep models; • Hands-on experience in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender; • Strong programming skills in C++, Python. Capability in implementing systems based on open-source software.

Applicants should provide the following information: • A comprehensive CV; • Academic transcripts of Bachelor and Master’s degree; • The name and contact details of two referees.

Interested candidates can email Binh-Son Hua (https://sonhua.github.io) for an informal discussion of the position. Applications will be reviewed on a rolling basis until the position has been filled.

London

Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

Where you will have an impact We're looking for an experienced Applied Scientist with expertise in Neural Radiance Fields (NeRFs) and Gaussian Splatting to join our Vision & Graphics team and advance our innovative neural simulator, Ghost Gym. This role is central to improving Ghost Gym's capabilities, utilizing state-of-the-art neural rendering techniques to craft photorealistic 4D worlds. You'll be at the forefront of developing and applying groundbreaking research to generate thousands of simulated scenarios. These scenarios are critical for training, testing, and debugging our end-to-end AI driving models, contributing significantly to the creation of safe and reliable AI driving technology. Your work will focus on improving the efficiency, realism, and dynamism of our simulations, especially for dynamic and outdoor environments, pushing the limits of current photorealistic visualization technologies.

Challenges you will own Conducting cutting-edge research in NeRFs, Gaussian splatting, and related technologies, with a focus on solving real-world challenges in 3D rendering Developing and implementing algorithms for efficient, high-quality 3D scene reconstruction and rendering, particularly for dynamic and outdoor environments Collaborating with cross-functional teams to integrate research findings into scalable, production-level solutions Staying abreast of the latest developments in the field, evaluating and incorporating state-of-the-art techniques into our workflows Potentially finding opportunities to publish research findings in top-tier journals and conferences, contributing to the scientific community and establishing Wayve as a leader in the field What you will bring to Wayve Essential Proven track record of research in NeRFs, Gaussian splatting, or closely related areas, demonstrated through publications or deployed applications Strong programming skills in Python with experience in deep learning frameworks such as PyTorch Solid foundation in mathematics and physics underlying 3D graphics and rendering techniques Excellent problem-solving skills and the ability to work independently as well as in a team environment Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment

Desirable Experience with dynamic scene reconstruction and rendering, particularly in outdoor environments Familiarity with parallel computing, GPU programming, and optimization techniques PhD or MSc in Computer Science, Computer Engineering, or a related field, with a focus on computer graphics, computer vision, or machine learning What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact Competitive compensation and benefits A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day

Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As a Sr. Fullstack Engineer, you will work on our platform engineering team playing a crucial role in enabling our research engineers to fine-tune our foundation models and streamline the machine learning process for our autonomous technology. You will work on developing products that empower our internal teams to maximize efficiency and innovation in our product. Specifically, you will:

• Build mission-critical tools for improving observability and scaling the entire machine-learning process.
• Use modern technologies to serve huge amounts of data, visualize key metrics, manage our data inventory, trigger backend data processing pipelines, and more.
• Work closely with people across the company to create a seamless UI experience.

※Location※ South Korea, Uiwang

※Description※ 1) AI Perception - RGB image based object/scene reconstruction (Nerf, GS, LRM) - Object detection / analysi - Image-Text multimodal model

2) Manipulation Vision - Development of vision-based Bimanual Manipulation using deep learning technology

3) On-Device AI - Development of lightweight deep learning model and on-device AI optimization technology

4) Mobile robot SLAM- Development of algorithms for Perception, SLAM, Motion control and Path planning

Redmond, Washington, United States

Overview We are seeking highly skilled and passionate research scientists to join Responsible & Open Ai Research (ROAR) in Azure Cognitive Services in Redmond, WA.

As a Principal Research Scientist, you will play a key role in advancing Responsible AI approaches to ensure safe releases of GenAI models such as GPT-4o, DALL-E, Sora, and beyond, as well as to expand and enhance the capability of Azure AI Content Safety Service.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities Conduct cutting-edge, deployment-driven research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of textual and multimodal AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues.

Enable the safe release of multimodal models from OpenAI in Azure OpenAI Service, expand and enhance the Azure AI Content Safety Service with new detection/mitigation technologies in text and multimodal content. Develop innovative approaches to address AI safety challenges for diverse customer scenarios.

Review business and product requirements and incorporate state-of-the-art research to formulate plans that will meet business goals. Identifies gaps and determines which tools, technologies, and methods to incorporate to ensure quality and scientific rigor. Proactively provides mentorship and coaching to less experienced and mid-level team members.

Location San Diego

Description

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, robotics and IOT devices. Qualcomm is creating building blocks for the intelligent edge.

We are part of Qualcomm AI Research, and we focus on advancing Edge AI machine learning technology – including model fine tuning, hardware acceleration, model quantization, model compression, network architecture search (NAS), edge inference and related fields. Come join us on this exciting journey. In this particular role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools. You will architect, design, develop, test, and deploy on- and off-device benchmarking workflows for model zoos.

Minimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.The successful applicant should have a strong theoretical background and proven hands-on experience with AI as modern software-, web-, and cloud-engineering.

Must have experience and skills: Strong theoretical background in AI and general ML techniques Proven hands-on experience with model training, inference, and evaluation. Proven hands-on experience with PyTorch, ONNX, TensorFlow, CUDA, and others. Experience developing data pipelines for ML/AI training and inferencing in the cloud. Prior experience in deploying containerized (web-) applications to IAAS environments such as AWS (preferred), Azure or GCP, backed by Dev-Ops and CI/CD technologies. Strong Linux command line skills. Strong experience with Docker and Git. Strong general analytical and debugging skills. Prior experience working in agile environments. Prior experience in collaborating with multi-disciplinary teams across time zones. Strong team player, communicator, presenter, mentor, and teacher. Preferred extra experience and skills: Prior experience with model quantization, profiling and running models on edge devices. Prior experience in developing full stack web applications using frameworks such as Ruby-on-Rails (preferred), Django, Phoenix/Elixir, Spring, Node.js or others. Knowledge of relational database design and optimization, hands on experience with running Postgres (preferred), MySQL or other relational databases in production Preferred qualifications: Bachelor's, Master's and/or PhD degree in Computer Science, Engineering, Information Systems, or related field and 2-5 years of work experience in Software Engineering, Systems Engineering, Hardware Engineering or related.

We are seeking a highly motivated candidate for a fully funded postdoctoral researcher position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain. The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The postdoctoral researcher is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting graduate or undergraduate students with technical guidance and engagement in other research activities such as paper reviews, reading group, workshop organization, etc.

The start date of the position is August 01, 2024. Contract duration is 1 year with the option of renewing for a second year. The successful candidate will require the following skills and knowledge: • PhD in Computer Science or related fields; • Strong tracked records in 3D computer graphics, 3D computer vision; • Hands-on experience in training deep models and generative models is required; • Hands-on experience and relevant skills in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender is desirable; • Strong programming skills in C++, Python. Capability in implementing systems from research papers and open-source software. • Additional background in math, statistics, or physics is an advantage.

Applicants should provide the following information: • A comprehensive CV including a full list of publications; • The name and contact details of two referees. One of the referees should be the applicant’s PhD supervisor; • Two representative papers by the applicant. Interested candidates should email their applications to Binh-Son Hua (https://sonhua.github.io) directly. Applications will be reviewed on a rolling basis until the position has been filled.