Vancouver

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 are seeking an experienced researcher to be a founding member of our Vancouver team! We are prioritising someone with experience actively participating in AI projects applied to autonomous driving or similar robotics or decision-making domains, inclusive, but not limited to the following specific areas:

Foundation models for robotics or embodied AI 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: behavioural and physical models of cars, people, and other dynamic agents Challenges you will own 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, evaluating and incorporating state-of-the-art techniques into our workflows. 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 Collaborate with cross-functional teams to integrate research findings into scalable, production-level solutions. 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, contributing to the scientific community and establishing Wayve as a leader in the field.

What you will bring to Wayve Proven track record of research in one or more of the topics above demonstrated through deployed applications or publications. Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch, numpy, pandas, etc. Experience bringing a machine learning research concept through the full ML development cycle 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 bringing an ML research concept through to production and at scale PhD in Computer Science, Computer Engineering, or a related field

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 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".

Location Mountain View, CA

Gatik is thrilled to be at CVPR! Come meet our team at booth 1831 to talk about how you could make an impact at the autonomous middle mile logistics company redefining the transportation landscape.

Who we are: Gatik, the leader in autonomous middle mile logistics, delivers goods safely and efficiently using its fleet of light & medium-duty trucks. The company focuses on short-haul, B2B logistics for Fortune 500 customers including Kroger, Walmart, Tyson Foods, Loblaw, Pitney Bowes, Georgia-Pacific, and KBX; enabling them to optimize their hub-and-spoke supply chain operations, enhance service levels and product flow across multiple locations while reducing labor costs and meeting an unprecedented expectation for faster deliveries. Gatik’s Class 3-7 autonomous box trucks are commercially deployed in multiple markets including Texas, Arkansas, and Ontario, Canada.

About the role:

We're currently looking for a tech lead with specialized skills in LiDAR, camera, and radar perception technologies to enhance our autonomous driving systems' ability to understand and interact with complex environments. In this pivotal role, you'll be instrumental in designing and refining the ML algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments. You will collaborate with a team of experts in AI, robotics, and software engineering to push the boundaries of what's possible in autonomous trucking.

What you'll do: - Design and implement cutting-edge perception algorithms for autonomous vehicles, focusing on areas such as sensor fusion, 3D object detection, segmentation, and tracking in complex dynamic environments - Design and implement ML models for real-time perception tasks, leveraging deep neural networks to enhance the perception capabilities of self-driving trucks - Lead initiatives to collect, augment, and utilize large-scale datasets for training and validating perception models under various driving conditions - Develop robust testing and validation frameworks to ensure the reliability and safety of the perception systems across diverse scenarios and edge cases - Conduct field tests and simulations to validate and refine perception algorithms, ensuring robust performance in real-world trucking routes and conditions - Work closely with the data engineering team to build and maintain large-scale datasets for training and evaluating perception models, including the development of data augmentation techniques

**Please click on the Apply link below to see the full job description and apply.

Inria (Grenoble), France

human-robot interaction, machine learning, computer vision, representation learning

We are looking for highly motivated students joining our team at INRIA. This project will take place in close collaboration between Inria team THOTH and the multidisciplinary institute in artificial intelligence (MIAI) in Grenoble

Topic: Human-robot systems are challenging because the actions of one agent can significantly influence the actions of others. Therefore, anticipating the partner's actions is crucial. By inferring beliefs, intentions, and desires, we can develop cooperative robots that learn to assist humans or other robots effectively. In this project we are in particular interested in estimating human intentions to enable collaborative tasks between humans and robots such as human-to-robot and robot-to-human handovers.

Contact pia.bideau@inria.fr The thesis will be jointly supervised by Pia Bideau (THOTH), Karteek Alahari (THOTH) and Xavier Alameda Pineda (RobotLearn).

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.

Engineering at Pinterest

Our Engineering team is at the core of bringing our platform to life for Pinners worldwide. Working collaboratively and cross-functionally with teams across the company, our engineers tackle growth-driving challenges to build an inspired and inclusive platform for all.

Our future of work is PinFlex

At Pinterest, we know that our best work happens when we feel most inspired. PinFlex promotes flexibility while prioritizing in-person moments to celebrate our culture and drive inspiration. We know that some work can be performed anywhere, and we encourage employees to work where they choose within their country or region, whether that’s at home, at a Pinterest office, or another virtual location. We believe that there is value in a distributed workforce but there are essential touch points for in-person collaboration that will create a big impact for our business and for development and connection.

Stop by booth #2100 to learn more about our open roles and our in-house generative AI foundation model that leverages the full power of our visual search and taste graph! Our engineers and recruiters are excited to connect with you!

At Zoox, you will collaborate with a team of world-class engineers with diverse backgrounds in areas such as AI, robotics, mechatronics, planning, control, localization, computer vision, rendering, simulation, distributed computing, design, and automated testing. You’ll master new technologies while working on code, algorithms, and research in your area of expertise to create and refine key systems and move Zoox forward.

Working at a startup gives you the chance to manifest your creativity and highly impact the final product.

ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

ASML’s Optical Sensing (Wafer Alignment Sensor and YieldStar) department in Wilton, Connecticut is seeking a Design Engineer to support and develop complex optical/photonic sensor systems used within ASML’s photolithography tools. These systems typically include light sources, detectors, optical/electro-optical components, fiber optics, electronics and signal processing software functioning in close collaboration with the rest of the lithography system. As a design engineer, you will design, develop, build and integrate optical sensor systems.

Role and Responsibilities Use general Physics, Optics, Software knowledge and an understanding of the sensor systems and tools to develop optical alignment sensors in lithography machines Have hands-on sills of building optical systems (e.g. imaging, testing, alignment, detector system, etc.) Have strong data analysis sills to evaluate sensor performance and troubleshooting Leadership:

Lead executing activities for determining problem root cause, execute complex tests, gather data and effectively communicate results on different levels of abstraction (from technical colleagues to high level managers) Lead engineers in various competencies (e.g. software, electronics, equipment engineering, manufacturing engineering, etc.) in support of feature delivery for alignment sensors Problem Solving: Troubleshooting complex technical problems Develop/debug data signal processing algorithms Develop and execute test plans in order to determine problem root cause Communications/Teamwork: Draw conclusions based on the input from different stakeholders Capability to clearly communicate the information on different level of abstraction Programming: Implement data analysis techniques into functioning MATLAB codes Optimization skills GUI building experience Familiarly with LabView and Python Some travel (up to 10%) to Europe, Asia and within the US can be expected

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.

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 Seattle, WA

Description Amazon's Compliance Shared Services (CoSS) is looking for a smart, energetic, and creative Sr Applied Scientist to extend and invent state-of-the-art research in multi-modal architectures, large language models across federated and continuous learning paradigms spread across multiple systems to join the Applied Research Science team in Seattle. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale that increase automation accuracy and coverage, and extend and invent new research as a key author to deliver re-usable foundational capabilities for automation.

You will analyze and process large amounts of image, text and tabular data from product detail pages, combine them with additional external and internal sources of multi-modal data, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms in federated and continuous learning modes that can be integrated and launched across multiple systems. You will partner with engineers and product managers across multiple Amazon teams to design new ML solutions implemented across worldwide Amazon stores for the entire Amazon product catalog.

Natick, MA, United States

The Company Cognex is a global leader in the exciting and growing field of machine vision.

The Team: Vision Algorithms, Advanced Vision Technology This position is in the Vision Algorithms Team of Advanced Vision Technology group, which is responsible for designing and developing the most sophisticated machine vision tools in the world. We combine custom hardware, specialized lighting, optics, and world-class vision algorithms to create software systems that are used to analyze imagery (intensity, color, density, Z-data, ID barcodes, etc.), to detect, identify and localize objects, to make measurements, to inspect for defects, and to read encoded data. Technology development is critical to the overall business to expand areas of application, improve performance, discover new algorithms, and to make use of new hardware and processing power. Engineers in this group typically have experience with image analysis, machine vision, or signal processing.

Job Summary: The Vision Algorithms team is looking for well-rounded, intelligent, creative, and motivated summer or fall intern with a passion for results! You will work with our senior engineers and technical leads on projects that advance our software development infrastructure and enhance our key technologies and customer experience. You will get mentorship on tackling technical challenges and opportunities to build a solid foundation for your career in Software Engineering, or Computer Vision and Artificial Intelligence.

Essential Functions: - Prototype and develop Vision (2D and ID) applications on top of Cognex products and technology. - Build internal tools or automated tests that can be used in software development or testing. - Understand our products and contribute to creating optimal solutions for customer applications in the automation industry. - High energy and motivated learner. Creative, motivated, and looking to work hard for a fast-moving company. - Strong analytical and problem-solving skills. - Strong programming skills in both C/C++ and Python are required. - Solid understanding of machine learning (ML) fundamentals and experience with ML frameworks like TensorFlow or PyTorch required. - Demonstrated projects or internships in AI/ML domain during academic or professional tenure is highly desirable. - Experience with embedded systems, Linux systems, vision/image-processing and optics all valued. - Background in 2D vision, 3D camera calibration & multi camera systems are preferred.

Minimum education and work experience required: Pursuing a MS, or Ph.D. from a top engineering school in EE, CS, or equivalent.

If you would like to meet the hiring manager at CVPR to discuss this opportunity, please email ahmed.elbarkouky@cognex.com

※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

Mountain View

Who we are Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning. With our multi-national world-class technical team, we’re building things differently.

We don’t think it’s scalable to tell an algorithm how to drive through hand-coded rules and expensive HD maps. Instead, we believe that using experience and data will allow our algorithms to be more intelligent: capable of easily adapting to new environments. Our aim is to be the future of self-driving cars: the first to deploy in 100 cities across the world bringing autonomy to everyone, everywhere.

Where you will have an impact: Science is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

As the first Research Manager in our Mountain View office, you will be responsible for managing & scaling a strong Science team which is building our Wayve Foundational Model in collaboration with other Wayve science teams in London and Vancouver. You will provide coaching and guidance to each of the researchers and engineers within your team and work with leaders across the company to ensure sustainable career growth for your team during a period of growth in the company. You will participate in our project-based operating model where your focus will be unlocking the potential of your team and its technical leaders to drive industry-leading impact. As part of your work, you will help identify the right projects to invest in, ensure the right allocation of resources to those projects, keep the team in good health, provide technical feedback to your team, share progress to build momentum, and build alignment and strong collaboration across the wider Science organisation. We are actively hiring and aim to substantially grow our research team over the next two years and you will be at the heart of this.

What you’ll bring to Wayve Essential: Prior experience as a manager of research teams (10-15+ people) with a clear career interest towards management Passionate about fostering personal and professional growth in individual team members Experience with roadmap planning, stakeholder management, requirements gathering and alignment with peers towards milestones and deliverables Strong knowledge of Machine Learning and related areas, such as Deep Learning, Natural Language Processing, Computer Vision, etc. Industry experience with machine learning technology development which has had real-world product impact Experience driving a team and technical project through the full lifecycle, ideally within the language, vision or multimodal space Passionate about bringing research concepts through to product Research and engineering fundamentals MS or PhD in Computer Science, Engineering, or similar experience

Desirable: Experience managing the execution of a technical product Good experience working in a project-based (“matrix”) operating environment Proven track record of successfully delivering research projects and publications Experience working with robotics, self-driving, AR/VR, or LLMs Our offer Competitive compensation, on-site chef and bar, lots of fun socials, workplace nursery scheme, comprehensive private health insurance and more! Immersion in a team of world-class researchers, engineers and entrepreneurs. A position to shape the future of autonomous driving, and thus bring about a real world deployment of a breakthrough technology. Help relocating/travelling to London, with visa sponsorship. Flexible working hours - we trust you to do your job well, at times that suit you and your team.

Overview We are seeking an exceptionally talented Postdoctoral Research Fellow to join our interdisciplinary team at the forefront of machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. This position is hosted by the Stanford Translational AI (STAI) in Medicine and Mental Health Lab (PI: Dr. Ehsan Adeli, https://stanford.edu/~eadeli), as part of the Department of Psychiatry and Behavioral Sciences at Stanford University. The postdoc will have the opportunity to directly collaborate with researchers and PIs within the Computational Neuroscience Lab (CNS Lab) in the School of Medicine and the Stanford Vision and Learning (SVL) lab in the Computer Science Department. These dynamic research groups are renowned for groundbreaking contributions to artificial intelligence and medical sciences.

Project Description The successful candidate will have the opportunity to work on cutting-edge projects aimed at building large-scale models for neuroimaging and neuroscience through innovative AI technologies and self-supervised learning methods. The postdoc will contribute to building a large-scale foundation model from brain MRIs and other modalities of data (e.g., genetics, videos, text). The intended downstream applications include understanding the brain development process during the early ages of life, decoding brain aging mechanisms, and identifying the pathology of different neurodegenerative or neuropsychiatric disorders. We use several public and private datasets including but not limited to the Human Connectome Project, UK Biobank, Alzheimer's Disease Neuroimaging Initiative (ADNI), Parkinson’s Progression Marker Initiative (PPMI), Open Access Series of Imaging Studies (OASIS), Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA), Adolescent Brain Cognitive Development (ABCD), and OpenNeuro.

Key Responsibilities Conduct research in machine learning, computer vision, and medical image analysis, with applications in neuroimaging and neuroscience. Develop and implement advanced algorithms for analyzing medical images and other modalities of medical data. Develop novel generative models. Develop large-scale foundation models. Collaborate with a team of researchers and clinicians to design and execute studies that advance our understanding of neurological disorders. Mentor graduate students (Ph.D. and MSc). Publish findings in top-tier journals and conferences. Contribute to grant writing and proposal development for securing research funding.

Qualifications PhD in Computer Science, Electrical Engineering, Neuroscience, or a related field. Proven track record of publications in high-impact journals and conferences including ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, MICCAI, Nature, and JAMA. Strong background in machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. Excellent programming skills in Python, C++, or similar languages and experience with ML frameworks such as TensorFlow or PyTorch. Ability to work independently and collaboratively in an interdisciplinary team. Excellent communication skills, both written and verbal.

Benefits Competitive salary and benefits package. Access to state-of-the-art facilities and computational resources. Opportunities for professional development and collaboration with leading experts in the field. Participation in international conferences and workshops. Working at Stanford University offers access to world-class research facilities and a vibrant intellectual community. The university provides numerous opportunities for interdisciplinary collaboration, professional development, and cutting-edge innovation. Additionally, being part of Stanford opens doors to a global network of leading experts and industry partners, enhancing both career growth and research impact.

Apply For full consideration, send a complete application via this form: https://forms.gle/KPQHPGGeXJcEsD6V6