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.

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.

Redmond, Washington, United States

Overview We are seeking a highly skilled and passionate Research Scientist to join our Responsible & OpenAI Research (ROAR) team in Azure Cognitive Services.

As a Research Scientist, you will play a key role in advancing the field of Responsible Artificial Intelligence (AI) to ensure safe releases of the rapidly advancing AI technologies, such as GPT-4, GPT-4V, DALL-E 3 and beyond, as well as to expand and enhance our standalone Azure AI Content Safety Service.

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 Conduct cutting-edge research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues. Contribute to the development of Responsible AI policies, guidelines, and best practices and ensure the practical implementation of these guidelines within various AI technology stacks across Microsoft, promoting a consistent approach to Responsible AI. Enable the safe release of new Azure OpenAI Service features, expand and enhance the Azure AI Content Safety Service with new detection technologies. Develop innovative approaches to address AI safety challenges for diverse customer scenarios. Other: Embody our Culture and Values

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 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.

Figma is growing our team of passionate people on a mission to make design accessible to all. Born on the Web, Figma helps entire product teams brainstorm, design and build better products — from start to finish. Whether it’s consolidating tools, simplifying workflows, or collaborating across teams and time zones, Figma makes the design process faster, more efficient, and fun while keeping everyone on the same page. From great products to long-lasting companies, we believe that nothing great is made alone—come make with us!

The AI Platform team at Figma is working on an exciting mission of expanding the frontiers of AI for creativity, and developing magical experiences in Figma products. This involves making existing features like search smarter, and incorporating new features using cutting edge Generative AI and deep learning techniques. We’re looking for engineers with a background in Machine Learning and Artificial Intelligence to improve our products and build new capabilities. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build ML models that will improve Figma’s design and collaboration tool.

What you’ll do at Figma:

• Driving fundamental and applied research in ML/AI using Generative AI, deep learning and classical machine learning, with Figma product use cases in mind.
• Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current models as well as enable the launch of entirely new AI-powered product features.
• Work in concert with other ML researchers, as well as product and infrastructure engineers to productionize new models and systems to power features in Figma’s design and collaboration tool.
• Expand the boundaries of what is possible with the current technology set and experiment with novel ideas.
• Publish scientific work on problems relevant to Figma in leading conferences like ICML, NeurIPS, CVPR etc.

We'd love to hear from you if you have:

• Recently obtained or is in the process of obtaining a PhD in AI, Computer Science or a related field. Degree must be completed prior to starting at Figma.
• Demonstrated expertise in machine learning with a publication record in relevant conferences, or a track record in applying machine learning techniques to products.
• Experience in Python and machine learning frameworks (such as PyTorch, TensorFlow or JAX).
• Experience building systems based on deep learning, natural language processing, computer vision, and/or generative models.
• Experience solving sophisticated problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
• Experience communicating and working across functions to drive solutions.

While not required, it’s an added plus if you also have:

• Experience working in industry on relevant AI projects through internships or past full time work.
• Publications in recent advances in AI like Large language models (LLMs), Vision language Models (VLMs) or diffusion models.

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.

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.

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.

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.

Seattle, US

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We’re passionate about empowering people to craft beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to building exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity Photoshop ART is seeking a Research Scientist to join our inpainting R&D team focused on making significant progress in image generation/restoration, low level vision, image editing with an eventual posture toward productization. Individuals in this role are expected to be expert in identified research areas such as artificial intelligence, machine learning, computer vision, and image processing. The ideal candidate will have a keen interest in producing new science to advance Adobe products.

What you'll Do Work towards long-term results-oriented research goals, while identifying intermediate achievements. Contribute to research that can be applied to Adobe product development. Help integrating novel research work into Adobe’s product. Lead and collaborate on research projects across different Adobe divisions. What you need to succeed Ph.D. and solid publications in machine learning, AI, computer science, statistics, or scene semantic understanding. Experience communicating research for public audiences of peers. Experience working in teams. Knowledge in a programming language. Preferred Qualification 2 years of professional full-time experience preferred, but not required 2+ year(s) of internship with primary emphasis on AI research in image generation, low level vision, image restoration, and segmentation Experience in collaboration with a team with varied strengths. 4+ First-author publications at peer-reviewed AI conferences (e.g. NIPS, CVPR, ECCV, ICML, ICLR, ICCV, and ACL). Experience in developing and debugging in Python. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely.

If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer.

Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, or veteran status.

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $129,400 -- $242,200 annually. Pay within this range varies by work location and may also depend on job-relate

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 Mountain View, CA

Gatik is thrilled to be at CVPR! Come meet our team at booth 1831 to talk about how you could make an impact at the autonomous middle mile logistics company redefining the transportation landscape.

Who we are: Gatik, the leader in autonomous middle mile logistics, delivers goods safely and efficiently using its fleet of light & medium-duty trucks. The company focuses on short-haul, B2B logistics for Fortune 500 customers including Kroger, Walmart, Tyson Foods, Loblaw, Pitney Bowes, Georgia-Pacific, and KBX; enabling them to optimize their hub-and-spoke supply chain operations, enhance service levels and product flow across multiple locations while reducing labor costs and meeting an unprecedented expectation for faster deliveries. Gatik’s Class 3-7 autonomous box trucks are commercially deployed in multiple markets including Texas, Arkansas, and Ontario, Canada.

About the role:

We're currently looking for a tech lead with specialized skills in LiDAR, camera, and radar perception technologies to enhance our autonomous driving systems' ability to understand and interact with complex environments. In this pivotal role, you'll be instrumental in designing and refining the ML algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments. You will collaborate with a team of experts in AI, robotics, and software engineering to push the boundaries of what's possible in autonomous trucking.

What you'll do: - Design and implement cutting-edge perception algorithms for autonomous vehicles, focusing on areas such as sensor fusion, 3D object detection, segmentation, and tracking in complex dynamic environments - Design and implement ML models for real-time perception tasks, leveraging deep neural networks to enhance the perception capabilities of self-driving trucks - Lead initiatives to collect, augment, and utilize large-scale datasets for training and validating perception models under various driving conditions - Develop robust testing and validation frameworks to ensure the reliability and safety of the perception systems across diverse scenarios and edge cases - Conduct field tests and simulations to validate and refine perception algorithms, ensuring robust performance in real-world trucking routes and conditions - Work closely with the data engineering team to build and maintain large-scale datasets for training and evaluating perception models, including the development of data augmentation techniques

**Please click on the Apply link below to see the full job description and apply.

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.