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

Location San Francisco, CA

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

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

Location Multiple Locations

Description Today, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous—expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.

Job Purpose & Responsibilities As a member of Qualcomm’s ML Systems Team, you will participate in two activities: Development and evolution of ML/AI compilers (production and exploratory versions) for efficient mappings of ML/AI algorithms on existing and future HW Analysis of ML/AI algorithms and workloads to drive future features in Qualcomm’s ML HW/SW offerings

Key Responsibilities: Contributing to the development and evolution of ML/AI compilers within Qualcomm Defining and implementing algorithms for mapping ML/AI workloads to Qualcomm HW Understanding trends in ML network design, through customer engagements and latest academic research, and how this affects both SW and HW design Creation of performance-driven simulation components (using C++, Python) for analysis and design of high-performance HW/SW algorithms on future SoCs Exploration and analysis of performance/area/power trade-offs for future HW and SW ML algorithms Pre-Silicon prediction of performance for various ML algorithms Running, debugging and analyzing performance simulations to suggest enhancements to Qualcomm hardware and software to tackle compute and system memory-related bottlenecks · Successful applications will work in cross-site, cross-functional teams.

Requirements: Demonstrated ability to learn, think and adapt in fast changing environment Detail-oriented with strong problem-solving, analytical and debugging skills Strong communication skills (written and verbal) Strong background in algorithm development and performance analysis is essential The following experiences would be significant assets: Strong object-oriented design principles Strong knowledge of C++ Strong knowledge of Python Experience in compiler design and development Knowledge of network model formats/platforms (eg. Pytorch, Tensorflow, ONNX) is an asset. On-silicon debug skills of high-performance compute algorithms · Knowledge of algorithms and data structures Knowledge of software development processes (revision control, CD/CI, etc.) · Familiarity with tools such as git, Jenkins, Docker, clang/MSVC Knowledge of computer architecture, digital circuits and event-driven transactional models/simulators

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

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.

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 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).

Vancouver, British Columbia, Canada

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

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

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

Location Sunnyvale, CA Seattle, WA New York, NY Cambridge, MA

Description The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with multimodal systems.

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

Redmond, Washington, United States

Overview We are seeking a Principal Research Engineer to join our organization and help improve steerability and control Large Language Models (LLMs) and other AI systems. Our team currently develops Guidance, a fully open-source project that enables developers to control language models more precisely and efficiently with constrained decoding.

As a Principal Research Engineer, you will play a crucial role in advancing the frontier of constrained decoding and imagining new application programming interface (APIs) for language models. If you’re excited about links between formal grammars and generative AI, deeply understanding and optimizing LLM inference, enabling more responsible AI without finetuning and RLHF, and/or exploring fundamental changes to the “text-in, text-out” API, we’d love to hear from you. Our team offers a vibrant environment for cutting-edge, multidisciplinary research. We have a long track record of open-source code and open publication policies, and you’ll have the opportunity to collaborate with world-leading experts across Microsoft and top academic institutions across 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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Develop and implement new constrained decoding research techniques for increasing LLM inference quality and/or efficiency. Example areas of interest include speculative execution, new decoding strategies (e.g. extensions to beam search), “classifier in the loop” decoding for responsible AI, improving AI planning, and explorations of attention-masking based constraints. Re-imagine the use and construction of context-free grammars (CFG) and beyond to fit Generative AI. Examples of improvements here include better tools for constructing formal grammars, extensions to Earley parsing, and efficient batch processing for constrained generation. Consideration of how these techniques are presented to developers – who may not be well versed in grammars and constrained generation -- in an intuitive, idiomatic programming syntax is also top of mind. Design principled evaluation frameworks and benchmarks for measuring the effects of constrained decoding on a model. Some areas of interest to study carefully include efficiency (token throughput and latency), generation quality, and impacts of constrained decoding on AI safety. Publish your research in top AI conferences and contribute your research advances to the guidance open-source project. Other

Embody our Culture and Values

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.

Location Sunnyvale, CA Bellevue, WA Seattle, WA

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

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

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

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

Location 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.