Redmond, Washington, United States

Overview We are seeking a Principal Research Engineer to join our organization and help improve steerability and control Large Language Models (LLMs) and other AI systems. Our team currently develops Guidance, a fully open-source project that enables developers to control language models more precisely and efficiently with constrained decoding.

As a Principal Research Engineer, you will play a crucial role in advancing the frontier of constrained decoding and imagining new application programming interface (APIs) for language models. If you’re excited about links between formal grammars and generative AI, deeply understanding and optimizing LLM inference, enabling more responsible AI without finetuning and RLHF, and/or exploring fundamental changes to the “text-in, text-out” API, we’d love to hear from you. Our team offers a vibrant environment for cutting-edge, multidisciplinary research. We have a long track record of open-source code and open publication policies, and you’ll have the opportunity to collaborate with world-leading experts across Microsoft and top academic institutions across the world.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Develop and implement new constrained decoding research techniques for increasing LLM inference quality and/or efficiency. Example areas of interest include speculative execution, new decoding strategies (e.g. extensions to beam search), “classifier in the loop” decoding for responsible AI, improving AI planning, and explorations of attention-masking based constraints. Re-imagine the use and construction of context-free grammars (CFG) and beyond to fit Generative AI. Examples of improvements here include better tools for constructing formal grammars, extensions to Earley parsing, and efficient batch processing for constrained generation. Consideration of how these techniques are presented to developers – who may not be well versed in grammars and constrained generation -- in an intuitive, idiomatic programming syntax is also top of mind. Design principled evaluation frameworks and benchmarks for measuring the effects of constrained decoding on a model. Some areas of interest to study carefully include efficiency (token throughput and latency), generation quality, and impacts of constrained decoding on AI safety. Publish your research in top AI conferences and contribute your research advances to the guidance open-source project. Other

Embody our Culture and Values

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 Science is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

As the first Research Manager in our Vancouver office, you will be responsible for managing & scaling a strong Science team in collaboration with other Wayve science teams in London and Mountain View. You will provide coaching and guidance to each of the researchers and engineers within your team and work with leaders across the company to ensure sustainable career growth for your team during a period of growth in the company. You will participate in our project-based operating model where your focus will be unlocking the potential of your team and its technical leaders to drive industry-leading impact. As part of your work, you will help identify the right projects to invest in, ensure the right allocation of resources to those projects, keep the team in good health, provide technical feedback to your team, share progress to build momentum, and build alignment and strong collaboration across the wider Science organisation. We are actively hiring and aim to substantially grow our research team over the next two years and you will be at the heart of this.

Challenges you will own Work closely with team members to develop career plans and growth trajectories based on each individual’s strengths and weaknesses and their own aspirations. Work closely with project leads to ensure team members are having strong impact and are set up for success. Work closely with project leads and Science leadership to ensure projects are resourced in a way that balances the needs of the business with the needs of the individuals. Offer coaching and technical mentorship to direct reports (especially project leads). Bring technical & project management expertise and experience to help accelerate our progress and decision-making. Challenge the status quo (both technical and organisational/process). Prioritize effectively and keep processes lean and effective. Partner with leadership to maintain a culture of cross-boundary collaboration, impact, innovation, and health. Grow the team as a hiring manager, to bring in complementary, diverse skill sets and backgrounds. Anticipate the needs of the business 6-24 months out, identify areas where additional resources are needed or we need to grow new domain expertise, and pitch this to leadership for investment. Contribute to the day-to-day running of the Science team’s operations and larger collaborative efforts.

ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

The Advanced Development Center at ASML in Wilton, Connecticut is seeking an Optical Data Analyst with expertise processing of images for metrology process development of ultra-high precision optics and ceramics. The Advanced Development Center (ADC) is a multi-disciplinary group of engineers and scientists focused on developing learning loop solutions, proto-typing of next generation wafer and reticle clamping systems and industrialization of proto-types that meet the system performance requirements.

Role and Responsibilities The main job function is to develop image processing, data analysis and machine learning algorithm and software to aid in development of wafer and reticle clamping systems to solve challenging engineering problems associated with achieving nanometer (nm) scale precision. You will be part of the larger Development and Engineering (DE) sector – where the design and engineering of ASML products happens.

As an Optical Data Analyst, you will: Develop/improve image processing algorithm to extract nm level information from scientific imaging equipment (e.g. interferometer, SEM, AFM, etc.) Integrate algorithms into image processing software package for analysis and process development cycles for engineering and manufacturing users Maintain version controlled software package for multiple product generations Perform software testing to identify application, algorithm and software bugs Validate/verify/regression/unit test software to ensure it meets the business and technical requirements Use machine learning models to predict trends and behaviors relating to lifetime and manufacturing improvements of the product Execute a plan of analysis, software and systems, to mitigate product and process risk and prevent software performance issues Collaborate with the design team in software analysis tool development to find solutions to difficult technical problems in an efficient manner Work with database structures and utilize capabilities Write software scripts to search, analyze and plot data from database Support query code to interrogate data for manufacturing and engineering needs Support image analysis on data and derive conclusions Travel (up to 10%) to Europe, Asia and within the US can be expected

Geomagical Labs is a 3D R&D lab, in partnership with IKEA. We create magical mixed-reality experiences for hundreds of millions of users, using computer vision, neural networks, graphics, and computational photography. Last year we launched IKEA Kreativ, and we’re excited for what’s next! We have an opening in our lab for a senior computer vision researcher, with 3D Reconstruction and Deep Learning expertise, to develop and improve the underlying algorithms powering our consumer products. We are looking for highly-motivated, creative, applied researchers with entrepreneurial drive, that are excited about building novel technologies and shipping them all the way to the hands of millions of customers!

Requirements: Ph.D. and 2+ years of experience, or Master's and 6+ years of experience, focused on 3D Computer Vision and Deep Learning. Experience in classical methods for 3D Reconstruction: SfM/SLAM, Multi-view Stereo, RGB-D Fusion. Experience in using Deep Learning for 3D Reconstruction and/or Scene Understanding, having worked in any of: Depth Estimation, Room Layout Estimation, NeRFs, Inverse Rendering, 3D Scene Understanding. Familiarity with Computer Graphics and Computational Photography. Expertise in ML frameworks and libraries, e.g. PyTorch. Highly productive in Python. Ability to architect and implement complex systems at the micro and macro level. Entrepreneurial: Adventurous, self-driven, comfortable under uncertainty, with a desire to make systems work end-to-end. Innovative; with a track record of patents and/or first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, SIGGRAPH, ISMAR, NeurIPS, ICLR etc. Experience in developing technologies that got integrated into products, as well as post-launch performance tracking and shipping improvements. [Bonus] Comfortable with C++.

Benefits: Join a mission-driven R&D lab, strategically backed by an influential global brand. Work in a dynamic team of computer vision, AI, computational photography, AR, graphics, and design professionals, and successful serial entrepreneurs. Opportunity to publish novel and relevant research. Fully remote work available to people living in the USA or Canada. Headquartered in downtown Palo Alto, California --- an easy walk from restaurants, coffee shops and Caltrain commuter rail. The USA base salary for this full-time position ranges from $180,000 to $250,000 determined by location, role, skill, and experience level. Geomagical Labs offers a comprehensive set of benefits, and for qualifying roles, substantial incentive grants, vesting annually.

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.

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).

A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. The initial appointment will be for one year with the possibility of extension. Review of applications will begin immediately and will continue until the position is filled. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

In the course of this interdisciplinary project, the postdoc will collaborate with a team of world-class scientists and clinicians with backgrounds in visual psychophysics, engineering, biostatistics, computer science, and ophthalmology. The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

The successful applicant will:

1. possess or be on track to complete a PhD or MD with background in computer science, mathematics, computational science, statistics, machine learning, deep learning, computer vision, image processing, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.

2. have strong programming skills (Python, R, MATLAB, C++, etc.) and in-depth understanding of statistics and machine learning. Experience with Linux clusters is a plus.

3. have a strong and productive publication record.

4. have a strong work ethic and time management skills along with the ability to work independently and within a multidisciplinary team as required.

Your application should include:

1. curriculum vitae

2. statement of past research accomplishments, career goal and how this position will help you achieve your goals

3. Two representative publications

4. contact information for three references

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab".

San Jose, CA

B GARAGE was founded in 2017 by a Ph.D. graduate from Stanford University. After having spent over five years researching robotics, computer vision, aeronautics, and drone autonomy, the founder and team set their minds on building a future where aerial robots would become an integral part of our daily lives without anyone necessarily piloting them. Together, our common goal is to redefine the user experience of drones and to expand the horizon for the use of drones.

Roles and Responsibilities

Design and develop perception for aerial robot and inventory recognition for warehouses by leveraging computer vision and deep learning techniques

Aid the computer vision team to deliver prototype and product in a timely manner

Collaborate with other teams within the company

Minimum Qualifications

M.S. degree in computer science, robotics, electrical engineering, or other engineering disciplines

10+ years of experience with computer vision and machine learning

Proficient in image processing algorithms and multiple view geometry using camera

Experience with machine learning architectures for object detection, segmentation, text recognition etc.

Proficient with ROS, C++, and Python

Experience with popular computer vision and GPU frameworks/libraries (e.g., OpenCV,TensorFlow, PyTorch, CUDA, cuDNN etc.)

Proficient in containerization technologies (Docker, Kubernetes) and container orchestration technologies

Experience in cloud computing platforms (AWS, GCP, etc.)

Experience with robots operating on real-time onboard processing

Self-motivated person who thrives in a fast-paced environment

Good problem solving and troubleshooting skills

Legally authorized to work in the United States

Optional Qualifications

Ph.D. degree in computer science, robotics, electrical engineering, or other engineering disciplines

Experience with scene reconstruction, bundle adjustment and factor graph optimization libraries

Experience with Javascript and massively parallel cloud computing technologies involving Kafka, Spark, MapReduce

Published research papers in CVPR, ICCV, ECCV, ICRA, IROS, etc.

Company Benefits

Competitive compensation packages

Medical, dental, vision, life insurance, and 401(k)

Flexible vacation and paid holidays

Complimentary lunches and snacks

Professional development reimbursement (online courses, conference, exhibit, etc.)

B GARAGE stands for an open and respectful corporate culture because we believe diversity helps us to find new perspectives.

B GARAGE ensures that all our members have equal opportunities – regardless of age, ethnic origin and nationality, gender and gender identity, physical and mental abilities, religion and belief, sexual orientation, and social background. We always ensure diversity right from the recruitment stage and therefore make hiring decisions based on a candidate’s actual competencies, qualifications, and business needs at the point of the time.

The Autonomy Software Metrics team is responsible for providing engineers and leadership at Zoox with tools to evaluate the behavior of Zoox’s autonomy stack using simulation. The team collaborates with experts across the organization to ensure a high safety bar, great customer experience, and rapid feedback to developers. The metrics team is responsible for evaluating the complete end-to-end customer experience through simulation, evaluating factors that impact safety, comfort, legality, road citizenship, progress, and more. You’ll be part of a passionate team making transportation safer, smarter, and more sustainable. This role gives you high visibility within the company and is critical for successfully launching our autonomous driving software.

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 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 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 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.

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 Sunnyvale, CA Bellevue, WA

Description Are you fueled by a passion for computer vision, machine learning and AI, and are eager to leverage your skills to enrich the lives of millions across the globe? Join us at Ring AI team, where we're not just offering a job, but an opportunity to revolutionize safety and convenience in our neighborhoods through cutting-edge innovation.

You will be part of a dynamic team dedicated to pushing the boundaries of computer vision, machine learning and AI to deliver an unparalleled user experience for our neighbors. This position presents an exceptional opportunity for you to pioneer and innovate in AI, making a profound impact on millions of customers worldwide. You will partner with world-class AI scientists, engineers, product managers and other experts to develop industry-leading AI algorithms and systems for a diverse array of Ring and Blink products, enhancing the lives of millions of customers globally. Join us in shaping the future of AI innovation at Ring and Blink, where exciting challenges await!