New York, United States

Overview Microsoft Research New York City (MSR NYC) is seeking applicants for a senior researcher position focusing on representation learning and efficient decision making with learned representations in the broader area of machine learning (ML) and artificial intelligence (AI), and in particular in the areas of interactive learning, this include deep learning with large foundation models over actions, and reinforcement learning.

Researchers in the ML/AI group cover a breadth of focus areas and research methodologies/approaches, spanning theoretical and empirical ML. We appreciate candidates with the potential to leverage/enhance the work of others in the group.

As a senior researcher, you will interact with our group's diverse array of researchers and practitioners, and contribute to ongoing research projects. We collaborate extensively with groups at other MSR locations and across Microsoft.

Microsoft Research (MSR) offers an exhilarating and supportive environment for cutting-edge, multidisciplinary research, both theoretical and empirical, with access to an extraordinary diversity of data sources, an open publications policy, and close links to top academic institutions around the world.

Applicants should have an established research track record, evidenced by conference or journal publications (or equivalent pieces of writing) and broader contributions to the research community. Applicants must have fulfilled their PhD degree requirements, including submission of their dissertation, prior to joining MSR NYC.

We are committed to building an inclusive, diverse, and pluralistic research environment and encourage applications from people of all backgrounds. We work collectively to make Microsoft Research a welcoming and productive space for all researchers.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we are dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Responsibilities As a senior researcher, you define your own research agenda in collaboration with other researchers, driving forward an effective program of basic, fundamental, and applied research. We highly value collaboration and building new ideas with members of the group and others. You may also have the direct opportunity to realize your ideas in products and services used worldwide.

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.

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

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

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)

The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

Location Santa Clara, CA

Description Amazon is looking for a passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Speech, Vision and Language technology.

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Machine Translation (MT), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).

As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding.

We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision.

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

Qualcomm's Multimedia R&D and Standards Group is seeking candidates for Video Compression Research Engineer positions. You will be part of world-renowned team of video compression experts. The team develops algorithms, hardware architectures, and systems for state-of-the-art applications of classical and machine learning methods in video compression, video processing, point cloud coding and processing, AR/VR and computer vision use cases. The successful candidate for this position will be a highly self-directed individual with strong creative and analytic skills and a passion for video compression technology. You will work on, but not be limited to, developing new applications of classical and machine learning methods in video compression improving state-of-the-art video codecs.

We are considering candidates with various levels of experience. We are flexible on location and open to hiring anywhere, preferred locations are USA, Germany and Taiwan.

Responsibilities: Contribute to the conception, development, implementation, and optimization of new algorithms extending existing techniques and systems allowing improved video compression. Initiate ideas, design and implement algorithms for superior hardware encoder performance, including perceptually based bit allocation. Develop new algorithms for deep learning-based video compression solutions. Represent Qualcomm in the related standardization forums: JVET, MPEG Video, and ITU-T/VCEG. Document and present new algorithms and implementations in various forms, including standards contributions, patent applications, conference and journal publications, presentations, etc. Ideal candidate would have the skills/experience below: Expert knowledge of the theory, algorithms, and techniques used in video and image coding. Knowledge and experience of video codecs and their test models, such as ECM, VVC, HEVC and AV1. Experience with deep learning structures CNN, RNN, autoencoder etc. and frameworks like TensorFlow/PyTorch. Track record of successful research accomplishments demonstrated through published papers, and/or patent applications in the fields of video coding or video processing. Solid programming and debugging skills in C/C++. Strong written and verbal English communication skills, great work ethic, and ability to work in a team environment to accomplish common goals. PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics or similar field, or equivalent practical experience.

Qualifications: PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics, or similar fields. 1+ years of experience with programming language such as C, C++, MATLAB, etc.

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.

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

Seattle, US

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We’re passionate about empowering people to craft beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to building exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity Photoshop ART is seeking a Research Scientist to join our inpainting R&D team focused on making significant progress in image generation/restoration, low level vision, image editing with an eventual posture toward productization. Individuals in this role are expected to be expert in identified research areas such as artificial intelligence, machine learning, computer vision, and image processing. The ideal candidate will have a keen interest in producing new science to advance Adobe products.

What you'll Do Work towards long-term results-oriented research goals, while identifying intermediate achievements. Contribute to research that can be applied to Adobe product development. Help integrating novel research work into Adobe’s product. Lead and collaborate on research projects across different Adobe divisions. What you need to succeed Ph.D. and solid publications in machine learning, AI, computer science, statistics, or scene semantic understanding. Experience communicating research for public audiences of peers. Experience working in teams. Knowledge in a programming language. Preferred Qualification 2 years of professional full-time experience preferred, but not required 2+ year(s) of internship with primary emphasis on AI research in image generation, low level vision, image restoration, and segmentation Experience in collaboration with a team with varied strengths. 4+ First-author publications at peer-reviewed AI conferences (e.g. NIPS, CVPR, ECCV, ICML, ICLR, ICCV, and ACL). Experience in developing and debugging in Python. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely.

If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer.

Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, or veteran status.

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $129,400 -- $242,200 annually. Pay within this range varies by work location and may also depend on job-relate

Tokyo, Tokyo-to, Japan

Overview As one of the world's leading industrial research laboratories, Microsoft Research (MSR) has more than 1,000 researchers and engineers working across the globe. In the past 30 years, Microsoft scientists have not only carried out world-class computer science research, but also transferred the advanced technologies into our products and services that have changed millions of people’s lives and ensured that Microsoft is at the forefront of digital transformation.

Part of Microsoft Research, Microsoft Research Asia (MSR Asia), established in 1998, is a leading research lab with major sites in Beijing, Shanghai and Vancouver. Over the years, technologies developed by MSR Asia have made a significant impact within Microsoft and also around the world, and new, innovative technologies are constantly being born from the lab. As one of the world-class research labs, MSRA offers an exhilarating, supportive, open and inclusive environment for top talents to create the future through their disruptive and cutting-edge research. (More information about Microsoft Research Lab - Asia - Microsoft Research).

Along with business growth, Microsoft Research Asia (MSRA) is increasing its presence in Japan, and looking for a Principal Research Manager who specializes in AI with an emphasis on Embodied AI and Robotics, AI Model innovations (NLP, vision, multi-modality), Societal AI, Wireless sensing, and Wellbeing. This is a unique opportunity to lead an ambitious research agenda and work with various teams to explore new applications of those research areas.

Responsibilities •As a leading and accomplished expert in a broad research area (e.g., Embodied AI and Robotics, AI Model, Multimedia and Vision), has a comprehensive understanding of the relevant literature, research methods, and business and academic context. •Defines and articulates a clear long-term research vision that is in line with MSRA strategic focus and drive research agenda landing with planned schedule •As a local representative, fosters cooperative relationships with local governments, academic communities, industry partners and business groups within Microsoft to establish MSRA presence locally and support future growth •Creates synergy among MSRA research groups in multiple locations to enable collaboration and creativity • As a people manager, hires and retains top talents. Deliveries success through empowerment and accountability

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 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 Vancouver office, you will be responsible for managing & scaling a strong Science team in collaboration with other Wayve science teams in London and Mountain View. 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.

Challenges you will own Work closely with team members to develop career plans and growth trajectories based on each individual’s strengths and weaknesses and their own aspirations. Work closely with project leads to ensure team members are having strong impact and are set up for success. Work closely with project leads and Science leadership to ensure projects are resourced in a way that balances the needs of the business with the needs of the individuals. Offer coaching and technical mentorship to direct reports (especially project leads). Bring technical & project management expertise and experience to help accelerate our progress and decision-making. Challenge the status quo (both technical and organisational/process). Prioritize effectively and keep processes lean and effective. Partner with leadership to maintain a culture of cross-boundary collaboration, impact, innovation, and health. Grow the team as a hiring manager, to bring in complementary, diverse skill sets and backgrounds. Anticipate the needs of the business 6-24 months out, identify areas where additional resources are needed or we need to grow new domain expertise, and pitch this to leadership for investment. Contribute to the day-to-day running of the Science team’s operations and larger collaborative efforts.