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 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).

Location Madrid, ESP

Description Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site.

The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content?

We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables.

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.

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

Location Seattle, WA Arlington, VA New York, NY San Francisco, CA

Description Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people.

The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale & speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable.

Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use this expertise and skills to identify, develop and evaluate the science and innovations necessary for Amazon, customers and partners to meet their long-term sustainability goals and commitments.

We’re seeking a Senior Principal Scientist for Sustainability and Climate AI to drive technical strategy and innovation for our long-term sustainability and climate commitments through AI & ML. You will serve as the strategic technical advisor to science, emerging tech, and climate pledge partners operating at the Director, VPs, and SVP level. You will set the next generation modeling standards for the team and tackle the most immature/complex modeling problems following the latest sustainability/climate sciences. Staying hyper current with emergent sustainability/climate science and machine learning trends, you'll be trusted to translate recommendations to leadership and be the voice of our interpretation. You will nurture a continuous delivery culture to embed informed, science-based decision-making into existing mechanisms, such as decarbonization strategies, ESG compliance, and risk management. You will also have the opportunity to collaborate with the Climate Pledge team to define strategies based on emergent science/tech trends and influence investment strategy. As a leader on this team, you'll play a key role in worldwide sustainability organizational planning, hiring, mentorship and leadership development.

If you see yourself as a thought leader and innovator at the intersection of climate science and tech, we’d like to connect with you.

Vancouver, British Columbia, Canada

Overview Microsoft Research (MSR), a leading industrial research laboratory comprised of over 1,000 computer scientists working across the United States, United Kingdom, China, India, Canada, and the Netherlands.

We are currently seeking a Senior Researcher in the area of  Artificial Specialized Intelligence located in Vancouver, British Columbia, with a keen interest in developing cutting-edge large foundation models and post-training techniques for different domains and scenarios. This is an opportunity to drive an ambitious research agenda while collaborating with diverse teams to push for novel applications of those areas.  
  Over the past 30 years, our scientists have not only conducted world-class computer science research but also integrated advanced technologies into our products and services, positively impacting millions of lives and propelling Microsoft to the forefront of digital transformation.

Responsibilities Conduct cutting-edge research in large foundation models, focusing on applying large foundation models in specific domain. Collaborate with cross-functional teams to integrate solutions into Artificial Intelligence (AI) -driven system. Develop and maintain research prototypes and software tools, ensuring that they are well-documented and adhere to best practices in software development. Publish research findings in top-tier conferences and journals and present your work at industry events. Collaborate with other AI researchers and engineers, sharing knowledge and expertise to foster a culture of innovation and continuous learning within the team.

Location San Diego

Description

Qualcomm AI Research is looking for world-class algorithm engineers in general domain machine learning, especially deep learning, generative AI, LLM, LVM. Come join a high-caliber team of engineers building advanced machine learning technology, best-in-class solutions, and user friendly model optimization tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet) to enable state-of-the-art networks to run on devices with limited power, memory, and computation.

Members of our team enjoy the opportunity to participate in cutting edge research while simultaneously contributing technology that will be deployed worldwide in our industry-leading devices. You will be part of a multi-disciplinary talented team working on on-device generative AI optimization. Collaborate in a cross-functional environment spanning hardware, software and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, autonomous vehicles, robotics, and IOT devices.

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 R&D work responsibility for this position focuses on the following: Algorithms research and development in the area of Generative AI, LVM, LLM, Multi-modality Efficient inference algorithms research and development, e.g. batching, KV caching, efficient attentions, long context, speculative decoding Advanced quantization algorithms research and development for complex generative models, e.g., gradient/non-gradient based optimization, equivalent/non-equivalent transformation, automatic mixed precision, hardware in loop Model compression, lossy or lossless, structural and neural search Optimization based learning and learning based optimization Generative AI system prototyping Apply solutions toward system innovations for model efficiency advancement on device as well as in the cloud Python, Pytorch programmer Preferred Qualifications: Master's degree in Computer Science, Engineering, Information Systems, or related field. PHD's degree is preferred. 2+ years of experience with Machine Learning algorithms or systems engineering or related work experience

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.

You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.

Location Sunnyvale, CA

Description Are you fueled by a passion for computer vision, machine learning and AI, and are eager to leverage your skills to enrich the lives of millions across the globe? Join us at Ring AI team, where we're not just offering a job, but an opportunity to revolutionize safety and convenience in our neighborhoods through cutting-edge innovation.

You will be part of a dynamic team dedicated to pushing the boundaries of computer vision, machine learning and AI to deliver an unparalleled user experience for our neighbors. This position presents an exceptional opportunity for you to pioneer and innovate in AI, making a profound impact on millions of customers worldwide. You will partner with world-class AI scientists, engineers, product managers and other experts to develop industry-leading AI algorithms and systems for a diverse array of Ring and Blink products, enhancing the lives of millions of customers globally. Join us in shaping the future of AI innovation at Ring and Blink, where exciting challenges await!

Captions is the AI-powered creative studio. Millions of creators around the world have used Captions to make their video content stand out from the pack and we're on a mission to empower the next billion.

Based in NYC, we are a team of ambitious, experienced, and devoted engineers, designers, and marketers. You'll be joining an early team where you'll have an outsized impact on both the product and company's culture.

We’re very fortunate to have some the best investors and entrepreneurs backing us, including Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, Lenny Rachitsky, and more.

Check out our latest milestone and our recent feature on the TODAY show and the New York Times.

** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) **

Responsibilities:

Conduct research and develop models to advance the state-of-the-art in generative computer vision technologies, with a focus on creating highly realistic digital faces, bodies, avatars.

Strive to set new standards in the realism of 3D digital human appearance, movement, and personality, ensuring that generated content closely resembles real-life scenarios.

Implement techniques to achieve high-quality results in zero-shot or few-shot settings, as well as customized avatars for different use cases while maintaining speed and accuracy.

Develop innovative solutions to enable comprehensive customization of video content, including the creation of digital people, modifying scenes, and manipulating actions and speech within videos.

Preferred Qualifications:

PhD in computer science (or related field) and/ or 5+ years of industry experience.

Strong academic background with a focus on computer vision and transformers, specializing in NeRFs, Gaussian Splatting, Diffusion, GANs or related areas.

Publication Record: Highly relevant publication history, with a focus on generating or manipulating realistic digital faces, bodies, expressions, body movements, etc. Ideal candidates will have served as the primary author on these publications.

Expertise in Deep Learning: Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with hands-on experience in designing, training, and deploying neural networks for multimodal tasks.

Strong understanding of Computer Science fundamentals (algorithms and data structures).

Benefits: Comprehensive medical, dental, and vision plans

Anything you need to do your best work

We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, Upstate NY, and Nashville with more planned in the future.

Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please note benefits apply to full time employees only.

The Autonomy Software Metrics team is responsible for providing engineers and leadership at Zoox with tools to evaluate the behavior of Zoox’s autonomy stack using simulation. The team collaborates with experts across the organization to ensure a high safety bar, great customer experience, and rapid feedback to developers. The metrics team is responsible for evaluating the complete end-to-end customer experience through simulation, evaluating factors that impact safety, comfort, legality, road citizenship, progress, and more. You’ll be part of a passionate team making transportation safer, smarter, and more sustainable. This role gives you high visibility within the company and is critical for successfully launching our autonomous driving software.

Gothenburg, Sweden

This fully-funded PhD position offers an opportunity to delve into the area of geometric deep learning within the broader landscape of machine learning and 3D computer vision. As a candidate, you'll have the chance to develop theoretical concepts and innovative methodologies while contributing to real-world imaging applications. Moreover, you will enjoy working in a diverse, collaborative, supportive and internationally recognized environment.

The PhD project centers on understanding and improving deep learning methods for 3D scene analysis and 3D generative diffusion models. We aim to explore new ways of encoding symmetries in deep learning models in order to scale up computations, a necessity for realizing truly 3D generative models for general scenes. We aim to explore the application of these models in key problems involving novel view synthesis and self-supervised learning.

If you are interested and present at CVPR, then feel free to reach out to Prof. Fredrik Kahl, head of the Computer Vision Group.

The Perception team at Zoox is responsible for developing the eyes and ears of our self driving car. Navigating safely and competently in the world requires us to detect, classify, track and understand several different attributes of all the objects around us that we might interact with, all in real time and with very high precision.

As a member of the Perception team at Zoox, you will be responsible for developing and improving state of the art machine learning techniques for doing everything from 2D/3D object detection, panoptic segmentation, tracking, to attribute classification. You will be working not just with our team of talented engineers and researchers in perception, but cross functionally with several teams including sensors, prediction and planning, and you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms.