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.

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

Location Sunnyvale, CA Bellevue, WA

Description Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique possibility to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. You will be part of a team committed to pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work on scale. This position requires experience with developing Multi-modal LLMs and Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.

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 San Diego

Description

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, robotics and IOT devices. Qualcomm is creating building blocks for the intelligent edge.

We are part of Qualcomm AI Research, and we focus on advancing Edge AI machine learning technology – including model fine tuning, hardware acceleration, model quantization, model compression, network architecture search (NAS), edge inference and related fields. Come join us on this exciting journey. In this particular role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools. You will architect, design, develop, test, and deploy on- and off-device benchmarking workflows for model zoos.

Minimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.The successful applicant should have a strong theoretical background and proven hands-on experience with AI as modern software-, web-, and cloud-engineering.

Must have experience and skills: Strong theoretical background in AI and general ML techniques Proven hands-on experience with model training, inference, and evaluation. Proven hands-on experience with PyTorch, ONNX, TensorFlow, CUDA, and others. Experience developing data pipelines for ML/AI training and inferencing in the cloud. Prior experience in deploying containerized (web-) applications to IAAS environments such as AWS (preferred), Azure or GCP, backed by Dev-Ops and CI/CD technologies. Strong Linux command line skills. Strong experience with Docker and Git. Strong general analytical and debugging skills. Prior experience working in agile environments. Prior experience in collaborating with multi-disciplinary teams across time zones. Strong team player, communicator, presenter, mentor, and teacher. Preferred extra experience and skills: Prior experience with model quantization, profiling and running models on edge devices. Prior experience in developing full stack web applications using frameworks such as Ruby-on-Rails (preferred), Django, Phoenix/Elixir, Spring, Node.js or others. Knowledge of relational database design and optimization, hands on experience with running Postgres (preferred), MySQL or other relational databases in production Preferred qualifications: Bachelor's, Master's and/or PhD degree in Computer Science, Engineering, Information Systems, or related field and 2-5 years of work experience in Software Engineering, Systems Engineering, Hardware Engineering or related.

As a systems engineer for perception safety, your primary responsibility will be to define and ensure the safety performance of the perception system. You will be working in close collaboration with perception algorithm and sensor hardware development teams.

Location Palo Alto, CA

Description Amazon is looking for talented Postdoctoral Scientists to join our Stores Foundational AI team for a one-year, full-time research position.

The Stores Foundational AI team builds foundation models for multiple Amazon entities, such as ASIN, customer, seller and brand. These foundation models are used in downstream applications by various partner teams in Stores. Our team also invest in building foundation model for image generation, optimized for product image generation. We leverage the latest development to create our solutions and innovate to push state of the art.

The Postdoc is expected to conduct research and build state-of-the-art algorithms in video understanding and representation learning in the era of LLMs. Specifically, Designing efficient algorithms to learn accurate representations for videos. Building extensive video understanding capabilities including various content classification tasks. Designing algorithms that can generate high-quality videos from set of product images. Improve the quality of our foundation models along the following dimensions: robustness, interpretability, fairness, sustainability, and privacy.

Location Seattle, WA

Description Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI)? Amazon's Consumer Electronics Technology (CE Tech) organization is redefining shopping experiences leveraging state of the art AI technologies. We are looking for a talented Sr. Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. You will help us shape the future of shopping experiences. As a member of our team, you'll work on cutting-edge projects that directly impact millions of customers, selling partners, and employees every single day. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.

Location Seattle, WA

Description To help a growing organization quickly deliver more efficient features to Prime Video customers, Prime Video’s READI organization is innovating on behalf of our global software development team consisting of thousands of engineers. The READI organization is building a team specialized in forecasting and recommendations. This team will apply supervised learning algorithms for forecasting multi-dimensional related time series using recurrent neural networks. The team will develop forecasts on key business dimensions and recommendations on performance and efficiency opportunities across our global software environment.

As a member of the team, you will apply your deep knowledge of machine learning to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them for customers, where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into designs with development teams and developing ready-to-use learning models. You consistently bring strong, data-driven business and technical judgment to decisions.

About the role As a detail-oriented and experienced Data Annotation QA Coordinator you will be responsible for both annotating in-house data-sets and ensuring the quality assurance of our outsourced data annotation deliveries.Your key responsibilities will include text, audio, image, and video annotation tasks, following detailed guidelines. To be successful in the team you will have to be comfortable working with standard tools and workflows for data annotation and possess the ability to manage projects and requirements effectively.

You will join a group of more than 40 Researchers and Engineers in the R&D department. This is an open, collaborative and highly supportive environment. We are all working together to build something big - the future of synthetic media and programmable video through Generative AI. You will be a central part of a dynamic and vibrant team and culture.

Please, note, this role is office-based. You will be working at our modern friendly office at the very heart of London.

Location Multiple Locations

Description The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. Qualcomm’s Cloud AI 100 accelerators are currently deployed at AWS / Cirrascale Cloud and at several large organizations. We are rapidly expanding our ML hardware and software solutions for large scale deployments and are hiring across many disciplines.

We are seeing to hire for multiple machine learning positions in the Qualcomm Cloud team. In this role, you will work with Qualcomm's partners to develop and deploy best in class ML applications (CV, NLP, GenAI, LLMs etc) based on popular frameworks such as PyTorch, TensorFlow and ONNX, that are optimized for Qualcomm's Cloud AI accelerators. The work will include model assessment of throughput, latency and accuracy, model profiling and optimization, end-to-end application pipeline development, integration with customer frameworks and libraries and responsibility for customer documentation, training, and demos. This candidate must possess excellent communication, leadership, interpersonal and organizational skills, and analytical skills.

This role will interact with individuals of all levels and requires an experienced, dedicated professional to effectively collaborate with internal and external stakeholders. The ideal candidate has either developed or deployed deep learning models on popular ML frameworks. If you have a strong appetite for technology and enjoy working in small, agile, empowered teams solving complex problems within a high energy, oftentimes chaotic environment then this is the role for you.

Minimum Qualifications: • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Applications Engineering, Software Development experience, or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Applications Engineering, Software Development experience, or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering, Software Development experience, or related work experience.

• 2+ years of experience with Programming Language such as C, C++, Java, Python, etc. • 1+ year of experience with debugging techniques.Key Responsibilities: Key contributor to Qualcomm’s Cloud AI GitHub repo and developer documentation. Work with developers in large organizations to Onboard them on Qualcomm’s Cloud AI ML stack improve and optimize their Deep Learning models on Qualcomm AI 100 deploy their applications at scale Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning. Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator. Optimize LLM/GenAI workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems. Partner with product management, hardware/software engineering to highlight customer progress, gaps in product features etc.

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.

※Location※ South Korea Seoul / Pangyo

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

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

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

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

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

As 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