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.

San Jose, CA

The Media Analytics team at NEC Labs America is seeking outstanding researchers with backgrounds in computer vision or machine learning. Candidates must possess an exceptional track record of original research and passion to create high impact products. Our key research areas include autonomous driving, open vocabulary perception, prediction and planning, simulation, neural rendering, agentic LLMs and foundational vision-language models. We have a strong internship program and active collaborations with academia. The Media Analytics team publishes extensively at top-tier venues such as CVPR, ICCV or ECCV.

To check out our latest work, please visit: https://www.nec-labs.com/research/media-analytics/

Qualifications: 1. PhD in Computer Science (or equivalent) 2. Strong publication record at top-tier computer vision or machine learning venues 3. Motivation to conduct independent research from conception to implementation.

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!

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

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

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

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 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

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".

B GARAGE was founded in 2017 by two PhD graduates from Stanford University. After having spent over five years researching robotics, computer vision, aeronautics, and drone autonomy, the co-founders 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.

The B GARAGE team is always looking for an enthusiastic, proactive, and collaborative Robotics and Automation Engineers to support the launch of intelligent aerial robots and autonomously sustainable ecosystems.

If you're interested in joining the B Garage team but don't see a role open that fits your background, apply to the general application and we'll reach out to discuss your career goals.

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

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in Computer Vision domain. You will also have experience within Generative AI space (GANs, Diffusion models and the like!).

👩‍💼 You will join a group of more than 50 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner and director of Science Prof. Vittorio Ferrari.

If you know and love DALL.E, MUSE, IMAGEN, MAKE-A-VIDEO, STABLE DIFFUSION and more - and you love large data, large compute and writing clean code, then we would love to talk to you.

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 Santa Clara, CA

Description Amazon is looking for a passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Speech, Vision and Language technology.

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Machine Translation (MT), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).

As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding.

We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision.

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.

You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.