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.

Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As a Research Engineer, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

• Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
• Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
• Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

Location New York, NY Seattle, WA Boston, MA

Description Climate Pledge Friendly helps customers discover and shop for products that are more sustainable. We partner with trusted sustainability certifications to highlight products that meet strict standards and help preserve the natural world. By shifting customer demand towards more sustainable products, we incentivize selling partners to build better selection, creating a virtuous cycle that yields significant environmental benefit at scale.

We are seeking a Senior Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. You will take the lead in conceptualizing, building, and launching models that significantly improve our shopping experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology.

You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. The types of initiatives you can expect to work on include a) personalized recommendations that help our customers find the right sustainable products on each shopping journey, b) automated solutions that combine ML/LLM and data mining to identify products that align with our sustainability goals and resonate with our customers' values, and c) models to measure the environmental and econometric impacts of sustainable shopping.

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 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.

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

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

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 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

Redmond, Washington, United States

Overview The Microsoft Research AI Frontiers group in Redmond is looking for a Senior Research Software Engineer to build state-of-the-art tools for evaluating and understanding foundation models, with a focus of real-world uses of Artificial Intelligence (AI). Our team conducts influential research published at top-tier venues in AI and ML (including NeurIPS, ICML, AAAI, and FAccT) and works within Microsoft’s Responsible AI ecosystem to impact our AI-driven technologies such as Azure, Office, and Bing.

We are seeking candidates with demonstrated ability for technical work in the space of large foundational models with proficient coding and machine learning skills. The preferred candidate is:

Passionate about rigorous evaluation, understanding, and development of foundational models.
Motivated to make successful research methods accessible to the AI community through prototypes, open-source libraries, and development tools. Proficient in design thinking and Object Oriented Design (OOD), building clean, modular, maintainable and user-friendly open-source ML Experienced in measuring and maximizing the impact of open-source libraries.

As a Senior Research Software Engineer, you will play a crucial role in designing and developing impactful, high quality and well-engineered frameworks to empower the scientific evaluation, understanding, and development of foundational models. You will work closely with a team of passionate researchers and engineers to make sure such frameworks are compatible with modern cloud platforms, Machine Learning (ML) frameworks and libraries, model architectures, and various data modalities. You will also play a central role in defining and running large-scale experiments that contribute to our team’s research.

We are looking for a team player interested in developing next-generation platforms and tools for Machine Learning (ML) as well as conducting state-of-the-art research. Topics of interest include but are not limited to rigorous evaluation and benchmarking, advances in AI interpretability, bias and fairness, and safety in real-world deployments. Our group takes a holistic approach to studying foundational models that includes a variety of data modalities (language, vision, multi-modal, and structured data) and modern model architectures. Candidates should demonstrate expertise in many of these aspects or show that they are interested in generalizing their skills into a variety of modalities and architectures.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re 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 Collaborate with a dedicated research and engineering team to design and develop ML frameworks for model evaluation and understanding.

• Define benchmarks and execute experiments for rigorous model evaluation and understanding.

• System Design and Object-Oriented Design: Envision elegant solutions and craft scalable and efficient systems to drive the success of our Machile Learning (ML) frameworks. Develop clean, modular, and maintainable code to shape the foundation of our evaluation framework.

• Work closely with partner engineering teams in both research and production.

• Mentor or onboard incoming engineering contributors and empower them to maximize the team’s impact.

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 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!

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 Madrid, ESP

Description At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (InTech) owns the enhancement and delivery of Amazon’s cutting-edge engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects.

You will be joining the Tools and Machine learning (Tamale) team. As part of InTech, Tamale strives to solve complex catalog quality problems using challenging machine learning and data analysis solutions. You will be exposed to cutting edge big data and machine learning technologies, along to all Amazon catalog technology stack, and you'll be part of a key effort to improve our customers experience by tackling and preventing defects in items in Amazon's catalog.

We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading machine learning solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.

We are seeking a highly motivated candidate for a fully funded postdoctoral researcher position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain. The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The postdoctoral researcher is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting graduate or undergraduate students with technical guidance and engagement in other research activities such as paper reviews, reading group, workshop organization, etc.

The start date of the position is August 01, 2024. Contract duration is 1 year with the option of renewing for a second year. The successful candidate will require the following skills and knowledge: • PhD in Computer Science or related fields; • Strong tracked records in 3D computer graphics, 3D computer vision; • Hands-on experience in training deep models and generative models is required; • Hands-on experience and relevant skills in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender is desirable; • Strong programming skills in C++, Python. Capability in implementing systems from research papers and open-source software. • Additional background in math, statistics, or physics is an advantage.

Applicants should provide the following information: • A comprehensive CV including a full list of publications; • The name and contact details of two referees. One of the referees should be the applicant’s PhD supervisor; • Two representative papers by the applicant. Interested candidates should email their applications to Binh-Son Hua (https://sonhua.github.io) directly. Applications will be reviewed on a rolling basis until the position has been filled.