The Perception team at Zoox is responsible for developing the eyes and ears of our self driving car. Navigating safely and competently in the world requires us to detect, classify, track and understand several different attributes of all the objects around us that we might interact with, all in real time and with very high precision.

As a member of the Perception team at Zoox, you will be responsible for developing and improving state of the art machine learning techniques for doing everything from 2D/3D object detection, panoptic segmentation, tracking, to attribute classification. You will be working not just with our team of talented engineers and researchers in perception, but cross functionally with several teams including sensors, prediction and planning, and you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms.

As a systems engineer for perception safety, your primary responsibility will be to define and ensure the safety performance of the perception system. You will be working in close collaboration with perception algorithm and sensor hardware development teams.

Location Seattle, WA

Description Amazon's Compliance Shared Services (CoSS) is looking for a smart, energetic, and creative Sr Applied Scientist to extend and invent state-of-the-art research in multi-modal architectures, large language models across federated and continuous learning paradigms spread across multiple systems to join the Applied Research Science team in Seattle. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale that increase automation accuracy and coverage, and extend and invent new research as a key author to deliver re-usable foundational capabilities for automation.

You will analyze and process large amounts of image, text and tabular data from product detail pages, combine them with additional external and internal sources of multi-modal data, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms in federated and continuous learning modes that can be integrated and launched across multiple systems. You will partner with engineers and product managers across multiple Amazon teams to design new ML solutions implemented across worldwide Amazon stores for the entire Amazon product catalog.

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.

Canberra/Australia

We are looking for new outstanding PhD students for the upcoming scholarship round (application is due on 31st August 2024) at the Australian National University (ANU is ranked #30 in the QS Ranking 2025) or possibly at another Australian universities.

We are looking for new PhD students to work on new problems that may span over (but are not limited to) "clever" adapting of Foundation Models, LLMs, diffusion models (LORAs etc.,), NERF, or design of Graph Neural Networks, design of new (multi-modal) Self-supervised Learning and Contrastive Learning Models (masked models, images, videos, text, graphs, time series, sequences, etc. ) or adversarial and/or federated learning or other contemporary fundamental/applied problems (e.g., learning without backprop, adapting FMs to be less resource hungry, planning and reasoning, hyperbolic geometry, protein property prediction, structured output generative models, visual relation inference, incremental/learning to learn problems, low shot, etc.)

To succeed, you need an outstanding publication record, e.g., one or more first-author papers in venues such CVPR, ICCV, ECCV, AAAI, ICLR, NeurIPS, ICML, IJCAI, ACM KDD, ACCV, BMVC, ACM MM, IEEE. Trans. On Image Processing, CVIU, IEEE TPAMI, or similar (the list is non-exhaustive). Non-first author papers will also help if they are in the mix. Some patents and/or professional experience in Computer Vision, Machine Learning or AI are a bonus. You also need a good GPA to succeed.

We are open to discussing your interests and topics, if you reach out, we can discuss what is possible. Yes, we have GPUs.

If you are interested, reach out for an informal chat with Dr. Koniusz. I am at CVPR if you want to chat?): piotr.koniusz@data61.csiro.au (or piotr.koniusz@anu.edu.au, www.koniusz.com)

Job Description Summary As a Research Engineer involved in the design of electrical machines, you will work in a collaborative team environment. You will be contributing to the development of advanced machine system concepts as well as their implementation for application to aircraft engine systems, power generation, and electric and hybrid vehicle applications. As part of a multi-disciplinary team, you will contribute to the planning, development, and transition of technologies from concept to products and/or services for GE Aerospace internal and external clients.

GE Aerospace Research will continue to play a vital role in supporting the industry through a historic recovery while shaping the future of flight. We invent the future of flight, lift people up and bring them home safely. Our commitment to lead the industry, to keep safe the flying public and the armed forces, and to lift up one another and our communities, remains our north star. Our purpose is what ties us to one another and gives meaning to our work.

Roles and Responsibilities

Work with customers to identify key system requirements.

Determine electrical machine (generators, motors, power delivery, and accessories') requirements by studying system and customer requirements.

Use system simulation tools, such as MATLAB, Simulink, and PLECS, to validate and refine control algorithms for a wide array of electric machines to ensure the system will perform in a manner consistent with the requirements.

Integrate the output of finite element analysis and other machine design software to determine and implement machine parameters within the system model.

Work closely with the electrical machine design team to make sure the physical machine meets requirements.

Develop and implement test procedures for electrical machine systems and document performance characteristics.

Deliver effective presentations, reports, and publications to Global Research, GE Businesses, government agencies, professional societies, and peer-reviewed journals.

Required Qualifications

PHD in Electrical Engineering or related field, with primary focus in controls applied to electric machines.

In-depth knowledge of electrical machines including electromagnetic, thermal as well as mechanical technology aspects.

Experience in a wide variety of machine topologies

Expertise in simulation tools such as finite elements, MATLAB (Simulink) and others such as PLECS.

US Citizenship required

Must be willing to work out of an office located in Niskayuna, NY

Must be 18 years or older

You must submit your application for employment on the careers page at www.gecareers.com to be considered.

Desired Characteristics

Experience in Automotive Hybrid Electrical or Aerospace Systems.

Strong interpersonal skills.

Strong analytical skills.

Ability to work across all functions/levels as part of a global team.

Ability to work under pressure and meet deadlines.

Excellent written and verbal communication skills.

Strong ties to the external technical community.

Entrepreneurial inclination

The base pay range for this position is 80,000 - 150,000 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary. This posting is expected to close on July 12, 2024

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, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

• Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
• Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
• Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

Inria (Grenoble), France

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

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

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

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

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 Seattle, WA Arlington, VA New York, NY San Francisco, CA

Description Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people.

The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale & speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable.

Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use this expertise and skills to identify, develop and evaluate the science and innovations necessary for Amazon, customers and partners to meet their long-term sustainability goals and commitments.

We’re seeking a Senior Principal Scientist for Sustainability and Climate AI to drive technical strategy and innovation for our long-term sustainability and climate commitments through AI & ML. You will serve as the strategic technical advisor to science, emerging tech, and climate pledge partners operating at the Director, VPs, and SVP level. You will set the next generation modeling standards for the team and tackle the most immature/complex modeling problems following the latest sustainability/climate sciences. Staying hyper current with emergent sustainability/climate science and machine learning trends, you'll be trusted to translate recommendations to leadership and be the voice of our interpretation. You will nurture a continuous delivery culture to embed informed, science-based decision-making into existing mechanisms, such as decarbonization strategies, ESG compliance, and risk management. You will also have the opportunity to collaborate with the Climate Pledge team to define strategies based on emergent science/tech trends and influence investment strategy. As a leader on this team, you'll play a key role in worldwide sustainability organizational planning, hiring, mentorship and leadership development.

If you see yourself as a thought leader and innovator at the intersection of climate science and tech, we’d like to connect with you.

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.

※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 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).

The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

Location Sunnyvale, CA Bellevue, WA

Description Are you 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!