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 Seattle, WA

Description Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis. You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields.

We are looking for talented Applied Scientists who are adept at a variety of skills, especially with computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team.

Location San Francisco, CA

Description Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.

You will be managing a team within the Music Machine Learning and Personalization organization that is responsible for developing, training, serving and iterating on models used for personalized candidate generation for both Music and Podcasts.

Location Seattle, WA

Description To help a growing organization quickly deliver more efficient features to Prime Video customers, Prime Video’s READI organization is innovating on behalf of our global software development team consisting of thousands of engineers. The READI organization is building a team specialized in forecasting and recommendations. This team will apply supervised learning algorithms for forecasting multi-dimensional related time series using recurrent neural networks. The team will develop forecasts on key business dimensions and recommendations on performance and efficiency opportunities across our global software environment.

As a member of the team, you will apply your deep knowledge of machine learning to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them for customers, where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into designs with development teams and developing ready-to-use learning models. You consistently bring strong, data-driven business and technical judgment to decisions.

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in Computer Vision domain. You will also have experience within Generative AI space (GANs, Diffusion models and the like!).

👩‍💼 You will join a group of more than 50 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner and director of Science Prof. Vittorio Ferrari.

If you know and love DALL.E, MUSE, IMAGEN, MAKE-A-VIDEO, STABLE DIFFUSION and more - and you love large data, large compute and writing clean code, then we would love to talk to you.

Location Palo Alto, CA

Description Amazon is looking for talented Postdoctoral Scientists to join our Stores Foundational AI team for a one-year, full-time research position.

The Stores Foundational AI team builds foundation models for multiple Amazon entities, such as ASIN, customer, seller and brand. These foundation models are used in downstream applications by various partner teams in Stores. Our team also invest in building foundation model for image generation, optimized for product image generation. We leverage the latest development to create our solutions and innovate to push state of the art.

The Postdoc is expected to conduct research and build state-of-the-art algorithms in video understanding and representation learning in the era of LLMs. Specifically, Designing efficient algorithms to learn accurate representations for videos. Building extensive video understanding capabilities including various content classification tasks. Designing algorithms that can generate high-quality videos from set of product images. Improve the quality of our foundation models along the following dimensions: robustness, interpretability, fairness, sustainability, and privacy.

London

Who are we?

Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class team of researchers and engineers, we’re using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, learning from experience and data.

Where you’ll have an impact

We are currently looking for people with research expertise in AI applied to autonomous driving or similar robotics or decision making domain, inclusive, but not limited to the following specific areas:

Foundation models for robotics Model-free and model-based reinforcement learning Offline reinforcement learning Large language models Planning with learned models, model predictive control and tree search Imitation learning, inverse reinforcement learning and causal inference Learned agent models: behavioral and physical models of cars, people, and other dynamic agents You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a key member of our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments. This encompasses many aspects of research across perception, prediction, planning, and control, including:

How to leverage our large, rich, and diverse sources of real-world driving data How to architect our models to best employ the latest advances in foundation models, transformers, world models, etc. Which learning algorithms to use (e.g. reinforcement learning, behavioural cloning) How to leverage simulation for controlled experimental insight, training data augmentation, and re-simulation How to scale models efficiently across data, model size, and compute, while maintaining efficient deployment on the car You also have the potential to contribute to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc. working in a world-class team to achieve this.

What you’ll bring to Wayve

Thorough knowledge of and 5+ years applied experience in AI research, computer vision, deep learning, reinforcement learning or robotics Ability to deliver high quality code and familiarity with deep learning frameworks (Python and Pytorch preferred) Experience leading a research agenda aligned with larger goals Industrial and / or academic experience in deep learning, software engineering, automotive or robotics Experience working with training data, metrics, visualisation tools, and in-depth analysis of results Ability to understand, author and critique cutting-edge research papers Familiarity with code-reviewing, C++, Linux, Git is a plus PhD in a relevant area and / or track records of delivering value through machine learning are a big plus. What we offer you

Attractive compensation with salary and equity Immersion in a team of world-class researchers, engineers and entrepreneurs A unique position to shape the future of autonomy and tackle the biggest challenge of our time Bespoke learning and development opportunities Relocation support with visa sponsorship Flexible working hours - we trust you to do your job well, at times that suit you and your time Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!

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 Sunnyvale, CA Bellevue, WA Seattle, WA

Description The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Science Manager with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems.

As an Applied Science Manager with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision.

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, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

• Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
• Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
• Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle 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.

Location Seattle, WA

Description Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI)? Amazon's Consumer Electronics Technology (CE Tech) organization is redefining shopping experiences leveraging state of the art AI technologies. We are looking for a talented Sr. Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. You will help us shape the future of shopping experiences. As a member of our team, you'll work on cutting-edge projects that directly impact millions of customers, selling partners, and employees every single day. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.

San Jose, CA

The Media Analytics team at NEC Labs America is seeking outstanding researchers with backgrounds in computer vision or machine learning. Candidates must possess an exceptional track record of original research and passion to create high impact products. Our key research areas include autonomous driving, open vocabulary perception, prediction and planning, simulation, neural rendering, agentic LLMs and foundational vision-language models. We have a strong internship program and active collaborations with academia. The Media Analytics team publishes extensively at top-tier venues such as CVPR, ICCV or ECCV.

To check out our latest work, please visit: https://www.nec-labs.com/research/media-analytics/

Qualifications: 1. PhD in Computer Science (or equivalent) 2. Strong publication record at top-tier computer vision or machine learning venues 3. Motivation to conduct independent research from conception to implementation.

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).

A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. The initial appointment will be for one year with the possibility of extension. Review of applications will begin immediately and will continue until the position is filled. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

In the course of this interdisciplinary project, the postdoc will collaborate with a team of world-class scientists and clinicians with backgrounds in visual psychophysics, engineering, biostatistics, computer science, and ophthalmology. The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

The successful applicant will:

1. possess or be on track to complete a PhD or MD with background in computer science, mathematics, computational science, statistics, machine learning, deep learning, computer vision, image processing, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.

2. have strong programming skills (Python, R, MATLAB, C++, etc.) and in-depth understanding of statistics and machine learning. Experience with Linux clusters is a plus.

3. have a strong and productive publication record.

4. have a strong work ethic and time management skills along with the ability to work independently and within a multidisciplinary team as required.

Your application should include:

1. curriculum vitae

2. statement of past research accomplishments, career goal and how this position will help you achieve your goals

3. Two representative publications

4. contact information for three references

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab".