Location Bellevue, WA

Description Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale.

This role is for the AFT AI team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.

We are looking for an Applied Scientist with expertise in computer vision. You will work alongside other CV scientists, engineers, product managers and various stakeholders to deploy vision models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying computer vision for real world problems - this is the team for you.

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.

Redmond, Washington, United States

Overview Do you want to shape the future of Artificial Intelligence (AI)? Do you have a passion for solving real-world problems with cutting-edge technologies?

The Human-AI eXperiences (HAX) team at Microsoft Research AI Frontiers is looking for exceptional candidates to advance the state-of-the-art in human-AI collaboration with a focus on leveraging the capabilities of people and foundation model-based agents and systems to solve real problems.

As a Principal Researcher on our team, you will:

Work on challenging and impactful projects in areas such as human-AI collaboration and teaming, foundation model-based systems, multi-agent systems, next generation AI experiences and responsible AI. Apply your skills and knowledge to build practical solutions to solve real problems and impact the world. Collaborate with other researchers and engineers across the company to amplify your impact and grow your career in a supportive and stimulating environment. We are looking for candidates who have:

A drive for real world impact, demonstrated by a passion to build and release prototypes or OSS frameworks.
Demonstrated track record of influential projects and publications in relevant fields and top-tier conferences and journals (such as NeurIPS, ICML, AAAI, CHI, UIST). Demonstrated interdisciplinary experience in applied machine learning, natural language processing, and human computer interaction including experience doing offline and online evaluations, and conducting user studies and user-centered research. Exceptional coding experience and hands-on experience working with large foundation models and related frameworks and toolkits. Familiarity with LLMs such as the OpenAI Generative Pre-Trained Transformers (GPT) models, LLAMA etc., model finetuning techniques (LORA, QLORA), prompting techniques (Chain of Thought, ReACT etc.) and model evaluation is beneficial.
A passion for innovation and creativity, evidenced by the ability to generate novel ideas, approaches, and solutions. A team player mindset, characterized by effective communication, collaboration, and feedback skills.

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 Perform cutting-edge research to solve real-world problems. Collaborate closely with other researchers, engineers, and product group partners on high-impact projects that deliver real-world impact to people and society. 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 Research Engineer for Optimization, you will focus on research and development related to the optimization of ML models on GPU’s or AI accelerators. You will use your judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems. Specifically, you will:

• Research, prototype and evaluate state of the art model optimization techniques and algorithms
• Characterize neural network quality and performance based on research, experiment and performance data and profiling
• Incorporate optimizations and model development best practices into existing ML development lifecycle and workflow.
• Define the technical vision and roadmap for DL model optimizations
• Write technical reports indicating qualitative and quantitative results to colleagues and customers
• Develop, deploy and optimize deep learning (DL) models on various GPU and AI accelerator chipsets/platforms

We are seeking a highly motivated candidate for a fully funded PhD 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 PhD student 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).

The start date of the position is September 01, 2024. The position is fully funded for 4 years by Science Foundation Ireland.

The successful candidate will require the following skills and knowledge: • Bachelor or Master in Computer Science or related fields; • Strong competence in computer graphics, computer vision; • Solid experience in academic research and publications is an advantage; • Additional background in math, statistics, or physics is an advantage. • Hands-on experience in training deep models; • Hands-on experience in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender; • Strong programming skills in C++, Python. Capability in implementing systems based on open-source software.

Applicants should provide the following information: • A comprehensive CV; • Academic transcripts of Bachelor and Master’s degree; • The name and contact details of two referees.

Interested candidates can email Binh-Son Hua (https://sonhua.github.io) for an informal discussion of the position. Applications will be reviewed on a rolling basis until the position has been filled.

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

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 Seattle, WA

Description Futures Design is the advanced concept design and incubation team within Amazon’s Device and Services Design Group (DDG). We are responsible for exploring and defining think (very) big opportunities globally and locally — so that we can better understand how new products and services might enrich the lives of our customers and so that product teams and leaders can align on where we're going and why we're going there. We focus on a 3–10+ year time frame, with the runway to invent and design category-defining products and transformational customer experiences. Working with Amazon business and technology partners, we use research, design, and prototyping to guide early product development, bring greater clarity to engineering goals, and develop a UX-grounded point of view.

We're looking for a Principal Design Technologist to join the growing DDG Futures Design team. You thrive in ambiguity and paradigm shifts– remaking assumptions of how customers engage, devices operate, and builders create. You apply deep expertise that spans design, technology, and product, grounding state-of-the-art emerging technologies through storytelling and a maker mindset. You learn and adapt technology trends to enduring customer problems through customer empathy, code, and iterative experimentation.

You will wear multiple hats to quickly assimilate customer problems, convert them to hypotheses, and test them using efficient technologies and design methods to build stakeholder buy-in. You’ll help your peers unlock challenging scenarios and mature the design studio’s ability to deliver design at scale across a breadth of devices and interaction modalities. You will work around limitations and push capabilities through your work. Your curiosity will inspire those around you and facilitate team growth, while your hands-on, collaborative nature will build trust with your peers and studio partners.

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.

Redwood City, CA; or Remote, US

We help make autonomous technologies more efficient, safer, and accessible.

Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks without the need for human annotation or simulation and is hardware-agnostic. We work with some of the world's largest automotive manufacturers and we've raised over $100M from Honda, Goodyear Ventures, Mando, and others to help us scale.

Our team is made up of people with a diverse set of experiences in software and academia. We work together towards one common goal: to integrate the software you'll help us build into hundreds of millions of vehicles.

We offer: - Competitive health insurance options - 401K plan management - Remote-friendly and flexible team culture - Free lunch and fully-stocked kitchen in our South Bay office - Additional perks: monthly wellness stipend, office set up allowance, company retreats, and more to come as we scale - The opportunity to work on one of the most interesting, impactful problems of the decade

Visit our website to apply for a position.

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 Seattle, WA

Description Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis. You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields.

We are looking for talented Applied Scientists who are adept at a variety of skills, especially with computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team.

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 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.

Inria (Grenoble), France

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

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

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

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