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.

Captions is the AI-powered creative studio. Millions of creators around the world have used Captions to make their video content stand out from the pack and we're on a mission to empower the next billion.

Based in NYC, we are a team of ambitious, experienced, and devoted engineers, designers, and marketers. You'll be joining an early team where you'll have an outsized impact on both the product and company's culture.

We’re very fortunate to have some the best investors and entrepreneurs backing us, including Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, Lenny Rachitsky, and more.

Check out our latest milestone and our recent feature on the TODAY show and the New York Times.

** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) **

Responsibilities:

Conduct research and develop models to advance the state-of-the-art in generative video technologies, focusing on areas such as video in-painting, super resolution, text-to-video conversion, background removal, and neural background rendering.

Design and develop advanced neural network models tailored for generative video applications, exploring innovative techniques to manipulate and enhance video content for storytelling purposes.

Explore new areas and techniques to enhance video storytelling, including research into novel generative approaches and their applications in video production and editing.

Create tools and systems that leverage machine learning, artificial intelligence, and computational techniques to generate, manipulate, and enhance video content, with a focus on usability and scalability.

Preferred Qualifications:

PhD in computer science or related field or 3+ years of industry experience.

Publication Record: Highly relevant publication history, with a focus on generative video techniques and applications. Ideal candidates will have served as the primary author on these publications.

Video Processing Skills: Strong understanding of video processing techniques, including video compression, motion estimation, and object tracking, with the ability to apply these techniques in generative video applications.

Expertise in Deep Learning: Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with hands-on experience in designing, training, and deploying neural networks for video-related tasks.

Strong understanding of Computer Science fundamentals (algorithms and data structures).

Benefits: Comprehensive medical, dental, and vision plans

Anything you need to do your best work

We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, Upstate NY, and Nashville with more planned in the future.

Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please note benefits apply to full time employees only.

Redmond, Washington, United States

Overview The Azure AI Platform (AIP) provides organizations across the world with the tooling and infrastructure needed to build and host AI workloads. The AI Platform organization is scaling rapidly, and we are establishing a world-class data analytics platform to support data-driven decision making through the organization.

We are looking to hire a Senior Data Scientist to join the newly formed AI Platform Analytics team. This individual will be responsible for collaborating with teams across AI Platform to establish trustworthy data sets and provide actionable insights and analysis.

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

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

Apply your knowledge in quantitative analysis, data mining, and the presentation of data to inform decision-making. Build data manipulation, processing, and data visualization tools and share these tools and your knowledge across the team, Cloud and AI, and Microsoft. Handle large amounts of data using various tools, including your own. Ensure high-quality and reliable data. Drive end-to-end projects by utilizing, applying and analyzing data to associated business problems. Engage with Upper Level Management by making key business decisions. Mentor other team members. Contribute to data-driven culture by collaborating with product and engineering teams across Azure to establish and share best practices Embody our culture and values

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.

New York, United States

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

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

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

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

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

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

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

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

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

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※ 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

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.

London

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're looking for an experienced Applied Scientist with expertise in Neural Radiance Fields (NeRFs) and Gaussian Splatting to join our Vision & Graphics team and advance our innovative neural simulator, Ghost Gym. This role is central to improving Ghost Gym's capabilities, utilizing state-of-the-art neural rendering techniques to craft photorealistic 4D worlds. You'll be at the forefront of developing and applying groundbreaking research to generate thousands of simulated scenarios. These scenarios are critical for training, testing, and debugging our end-to-end AI driving models, contributing significantly to the creation of safe and reliable AI driving technology. Your work will focus on improving the efficiency, realism, and dynamism of our simulations, especially for dynamic and outdoor environments, pushing the limits of current photorealistic visualization technologies.

Challenges you will own Conducting cutting-edge research in NeRFs, Gaussian splatting, and related technologies, with a focus on solving real-world challenges in 3D rendering Developing and implementing algorithms for efficient, high-quality 3D scene reconstruction and rendering, particularly for dynamic and outdoor environments Collaborating with cross-functional teams to integrate research findings into scalable, production-level solutions Staying abreast of the latest developments in the field, evaluating and incorporating state-of-the-art techniques into our workflows Potentially finding opportunities to publish research findings in top-tier journals and conferences, contributing to the scientific community and establishing Wayve as a leader in the field What you will bring to Wayve Essential Proven track record of research in NeRFs, Gaussian splatting, or closely related areas, demonstrated through publications or deployed applications Strong programming skills in Python with experience in deep learning frameworks such as PyTorch Solid foundation in mathematics and physics underlying 3D graphics and rendering techniques 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 with dynamic scene reconstruction and rendering, particularly in outdoor environments Familiarity with parallel computing, GPU programming, and optimization techniques PhD or MSc in Computer Science, Computer Engineering, or a related field, with a focus on computer graphics, computer vision, or machine learning 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 A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day

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 Seattle, WA Palo Alto, CA

Description Amazon’s product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on an AI-first initiative to continue to improve the way we do search through the use of large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced multi-modal deep-learning models on very large scale datasets, specifically through the use of advanced systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge Computer Vision and Deep Learning technologies and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: * How can multi-modal inputs in deep-learning models help us deliver delightful shopping experiences to millions of Amazon customers? * Can combining multi-modal data and very large scale deep-learning models help us provide a step-function improvement to the overall model understanding and reasoning capabilities? We are looking for exceptional scientists who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.

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

Location Amsterdam, Netherlands

Description

At Qualcomm AI Research, we are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we’re pushing the boundaries of what’s possible and shaping the future of AI.

As Principal Machine Learning Researcher at Qualcomm, you conduct innovative research in machine learning, deep learning, and AI that advances the state-of-the-art. · You develop and quickly iterate on innovative research ideas, and prototype and implement them in collaboration with other researchers and engineers. · You are on top of and actively shaping the latest research in the field and publish papers at top scientific conferences. · You help define and shape our research vision and planning within and across teams and are passionate at execution. · You engage with leads and stakeholders across business units on how to translate research progress into business impact. · You work in one or more of the following research areas: Generative AI, foundation models (LLMs, LVMs), reinforcement learning, neural network efficiency (e.g., quantization, conditional computation, efficient HW), on-device learning and personalization, and foundational AI research.

Working at Qualcomm means being part of a global company (headquartered in San Diego) that fosters a diverse workforce and puts emphasis on the learning opportunities and professional development of its employees. You will work closely with researchers that have published at major conferences, work on campus at the University of Amsterdam, where you have the opportunity to collaborate with academic researchers through university partnerships such as the QUVA lab, and live in a scenic, vibrant city with a healthy work/life balance and a diversity of cultural activities. In addition, you can join plenty of mentorship, learning, peer, and affinity group opportunities within the company. In this way you can easily develop personal and professional skills in your areas of interest. You’re empowered to start your own initiatives and, in doing so, collaborate with colleagues in offices across teams and countries.

Minimum qualifications: · PhD or Master’s degree in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience. · 8+ years of experience in machine learning and AI, and experience in working in an academic or industry research lab. · Strong drive to continuously improve beyond the status quo in translating new ideas into innovative solutions. · Track record of scientific leadership by having published impactful work at major conferences in machine learning, computer vision, or NLP (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP, NAACL, etc.). · Programming experience in Python and experience with standard deep learning toolkits.

Preferred qualifications: · Hands-on experience with foundation models (LLMs, LVMs) and reinforcement learning. · Proven experience in technology and team leadership, and experience with cross-functional stakeholder engagements. · Experience in writing clean and maintainable code for research-internal use (no product development). · Aptitude for guiding and mentoring more junior researchers.