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.

Location Sunnyvale, CA Bellevue, WA

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!

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

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.

Location San Diego

Description

At Qualcomm, we are transforming the automotive industry with our Snapdragon Digital Chassis and building the next generation software defined vehicle (SDV).

Snapdragon Ride is an integral pillar of our Snapdragon Digital Chassis, and since its launch it has gained momentum with a growing number of global automakers and Tier1 suppliers. Snapdragon Ride aims to address the complexity of autonomous driving and ADAS by leveraging its high-performance, power-efficient SoC, industry-leading artificial intelligence (AI) technologies and pioneering vision and drive policy stack to deliver a comprehensive, cost and energy efficient systems solution.

Enabling safe, comfortable, and affordable autonomous driving includes solving some of the most demanding and challenging technological problems. From centimeter-level localization to multimodal sensor perception, sensor fusion, behavior prediction, maneuver planning, and trajectory planning and control, each one of these functions introduces its own unique challenges to solve, verify, test, and deploy on the road.

We are looking for smart, innovative and motivated individuals with strong theory background in deep learning, advanced signal processing, probability & algorithms and good implementation skills in python/C++. Job responsibilities include design and development of novel algorithms for solving complex problems related to behavior prediction for autonomous driving, including trajectory and intention prediction. Develop novel deep learning models to predict trajectories for road users and optimize them to run-in real-time systems. Work closely with sensor fusion and planning team on defining requirements and KPIs. Work closely with test engineers to develop test plans for validating performance in simulations and real-world testing.

Minimum Qualifications: • Bachelor's degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 6+ years of Systems Engineering or related work experience. OR Master's degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 5+ years of Systems Engineering or related work experience. OR PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 4+ years of Systems Engineering or related work experience.Preferred Qualifications: Ph.D + 2 years industry experience in behavior and trajectory prediction Proficient in variety of deep learning models like CNN, Transformer, RNN, LSTM, VAE, GraphCNN etc Experience working with NLP Deep Learning Networks Proficient in state of the art in machine learning tools (pytorch, tensor flow) 3+ years of experience with Programming Language such as C, C++, Python, etc. 3+ years Systems Engineering, or related work experience in the area of behavior and trajectory prediction. Experience working with, modifying, and creating advanced algorithms Analytical and scientific mindset, with the ability to solve complex problems. Experience in Autonomous driving, Robotics, XR/AR/VR Experience with robust software design for safety-critical systems Excellent written and verbal communication skills, ability to work with a cross-functional team

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.

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 on our Motion Planning team, 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
• Develop our planner behavior and trajectories in collaboration with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms
• 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

※Location※ South Korea Seoul / Pangyo

※Description※ 1) Deep learning compression and optimization - Development of algorithms for compression and optimization of deep learning networks - Perform deep learning network embedding (requires understanding of HW platform)

2) AD vision recognition SW - Development of deep learning recognition technology based on sensors such as cameras - Development of pre- and post-processing algorithms and function output - Development of optimization of image recognition algorithm

3) AD decision/control SW - Development of information-based map generation technology recognized by many vehicles - Development of learning-based nearby object behavior prediction model - Development of driving mode determination and collision prevention function of Lv 3 autonomous driving system

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

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)

Redmond, Washington, United States

Overview Microsoft Research (MSR) AI Frontiers lab is seeking applications for the position of Senior Research Engineer – Generative AI to join their team in Redmond, WA and New York City, NY.

The mission of the AI Frontiers lab is to expand the pareto frontier of AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. Some of our projects include work on Small Language Models (e.g. Phi, Orca), foundation models for actions (e.g., in gaming, robotics, and Office productivity tools) and Multi-Agent AI (e.g. AutoGen).

We are seeking Senior Research Engineers to join our team and contribute to the advancement of Generative AI and Large Language Models (LLMs) technologies. As a Research Engineer, you will play a crucial role in developing, improving, and exploring the capabilities of Generative AI models. Your work will have a significant impact on the development of cutting-edge technologies, advancing state-of-the-art and providing practical solutions to real-world problems.  

Our ongoing research areas encompass but are not limited to:

Pre-training: especially of language models, action models and multimodal models Alignment and Post-training: e.g., Instruction tuning and reinforcement learning from feedback Continual Learning: Enabling LLMs to evolve and adapt over time and learn from previous experiences human interactions Specialization: Tailoring models to meet application-specific requirements Orchestration and multi-agent systems: automated orchestration between multiple agents incorporating human feedback and oversight

Microsoft Research (MSR) offers a vibrant environment for cutting-edge, multidisciplinary, research, including access to diverse, real-world problems and data, opportunities for experimentation and real-world impact, an open publication policy, and close links to top academic institutions around the world.

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.

Embody our Culture and Values

Responsibilities As a Senior Research Engineer in AI Frontiers, you will design, develop, execute, and implement technology research projects in collaboration with other researchers, engineers, and product groups.

As a member of a word-class research organization, you will be a part of research breakthroughs in the field and will be given an opportunity to realize your ideas in products and services used worldwide.

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).

Geomagical Labs is a 3D R&D lab, in partnership with IKEA. We create magical mixed-reality experiences for hundreds of millions of users, using computer vision, neural networks, graphics, and computational photography. Last year we launched IKEA Kreativ, and we’re excited for what’s next! We have an opening in our lab for a senior computer vision researcher, with 3D Reconstruction and Deep Learning expertise, to develop and improve the underlying algorithms powering our consumer products. We are looking for highly-motivated, creative, applied researchers with entrepreneurial drive, that are excited about building novel technologies and shipping them all the way to the hands of millions of customers!

Requirements: Ph.D. and 2+ years of experience, or Master's and 6+ years of experience, focused on 3D Computer Vision and Deep Learning. Experience in classical methods for 3D Reconstruction: SfM/SLAM, Multi-view Stereo, RGB-D Fusion. Experience in using Deep Learning for 3D Reconstruction and/or Scene Understanding, having worked in any of: Depth Estimation, Room Layout Estimation, NeRFs, Inverse Rendering, 3D Scene Understanding. Familiarity with Computer Graphics and Computational Photography. Expertise in ML frameworks and libraries, e.g. PyTorch. Highly productive in Python. Ability to architect and implement complex systems at the micro and macro level. Entrepreneurial: Adventurous, self-driven, comfortable under uncertainty, with a desire to make systems work end-to-end. Innovative; with a track record of patents and/or first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, SIGGRAPH, ISMAR, NeurIPS, ICLR etc. Experience in developing technologies that got integrated into products, as well as post-launch performance tracking and shipping improvements. [Bonus] Comfortable with C++.

Benefits: Join a mission-driven R&D lab, strategically backed by an influential global brand. Work in a dynamic team of computer vision, AI, computational photography, AR, graphics, and design professionals, and successful serial entrepreneurs. Opportunity to publish novel and relevant research. Fully remote work available to people living in the USA or Canada. Headquartered in downtown Palo Alto, California --- an easy walk from restaurants, coffee shops and Caltrain commuter rail. The USA base salary for this full-time position ranges from $180,000 to $250,000 determined by location, role, skill, and experience level. Geomagical Labs offers a comprehensive set of benefits, and for qualifying roles, substantial incentive grants, vesting annually.

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

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 the MLE, you will collaborate with researchers to perform research operations using existing infrastructure. You will use your judgment in complex scenarios and help apply standard techniques to various technical problems. Specifically, you will:

• Characterize neural network quality, failure modes, and edge cases based on research data
• Maintain awareness of current trends in relevant areas of research and technology
• Coordinate with researchers and accurately convey the status of experiments
• Manage a large number of concurrent experiments and make accurate time estimates for deadlines
• Review experimental results and suggest theoretical or process improvements for future iterations
• Write technical reports indicating qualitative and quantitative results to external parties