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 Microsoft Research (MSR) AI Frontiers lab is seeking applications for the position of Principal Researcher – Generative AI to join their team.

The mission of the AI Frontiers lab is to expand the pareto frontier of Artificial Intelligence (AI) capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. Some of our projects include work on Small Language Models (e.g. Phi, Orca) and Multi-Agent AI (e.g. AutoGen).

We are seeking a Principal Researcher – Generative AI to join our team and lead efforts on the advancement of Generative AI and Large Language Models (LLMs) technologies. As a Principal Researcher – Generative AI, you will play a crucial role in leading, developing, improving, and exploring the capabilities of Generative AI models. Your work will have a significant impact on the development of cutting-edge technologies, advancing state-of-the-art and providing practical solutions to real-world problems.  

Our ongoing research areas encompass but are not limited to:

Pre-training: especially of small language and multimodal models Alignment and Post-training: e.g., Instruction tuning and reinforcement learning from feedback Continual Learning: Enabling LLMs to evolve and adapt over time and learn from previous experiences human interactions Specialization: Tailoring LLMs to meet application-specific requirements Orchestration and multi-agent systems: automated orchestration between multiple agents incorporating human feedback and oversight

MSR offers a vibrant environment for cutting-edge, multidisciplinary, research, including access to diverse, real-world problems and data, opportunities for experimentation and real-world impact, an open publication policy, and close links to top academic institutions around 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 You will perform cutting-edge research in collaboration with other researchers, engineers, and product groups.
As a member of a word-class research organization, you will be a part of research breakthroughs in the field and will be given an opportunity to realize your ideas in products and services used worldwide. Embody our culture and values.

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 on our Motion Planning team, 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
• Develop our planner behavior and trajectories in collaboration with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms
• 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

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.

Gothenburg, Sweden

This fully-funded PhD position offers an opportunity to delve into the area of geometric deep learning within the broader landscape of machine learning and 3D computer vision. As a candidate, you'll have the chance to develop theoretical concepts and innovative methodologies while contributing to real-world imaging applications. Moreover, you will enjoy working in a diverse, collaborative, supportive and internationally recognized environment.

The PhD project centers on understanding and improving deep learning methods for 3D scene analysis and 3D generative diffusion models. We aim to explore new ways of encoding symmetries in deep learning models in order to scale up computations, a necessity for realizing truly 3D generative models for general scenes. We aim to explore the application of these models in key problems involving novel view synthesis and self-supervised learning.

If you are interested and present at CVPR, then feel free to reach out to Prof. Fredrik Kahl, head of the Computer Vision Group.

Location 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.

At Zoox, you will collaborate with a team of world-class engineers with diverse backgrounds in areas such as AI, robotics, mechatronics, planning, control, localization, computer vision, rendering, simulation, distributed computing, design, and automated testing. You’ll master new technologies while working on code, algorithms, and research in your area of expertise to create and refine key systems and move Zoox forward.

Working at a startup gives you the chance to manifest your creativity and highly impact the final product.

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.

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

※Location※ South Korea, Uiwang

※Description※ 1) AI Perception - RGB image based object/scene reconstruction (Nerf, GS, LRM) - Object detection / analysi - Image-Text multimodal model

2) Manipulation Vision - Development of vision-based Bimanual Manipulation using deep learning technology

3) On-Device AI - Development of lightweight deep learning model and on-device AI optimization technology

4) Mobile robot SLAM- Development of algorithms for Perception, SLAM, Motion control and Path planning

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

Redmond, Washington, United States

Overview Do you want to shape the future of Artificial Intelligence (AI)? Do you have a passion for solving real-world problems with cutting-edge technologies?

The Human-AI eXperiences (HAX) team at Microsoft Research AI Frontiers is looking for exceptional candidates to advance the state-of-the-art in human-AI collaboration with a focus on leveraging the capabilities of people and foundation model-based agents and systems to solve real problems.

As a Principal Researcher on our team, you will:

Work on challenging and impactful projects in areas such as human-AI collaboration and teaming, foundation model-based systems, multi-agent systems, next generation AI experiences and responsible AI. Apply your skills and knowledge to build practical solutions to solve real problems and impact the world. Collaborate with other researchers and engineers across the company to amplify your impact and grow your career in a supportive and stimulating environment. We are looking for candidates who have:

A drive for real world impact, demonstrated by a passion to build and release prototypes or OSS frameworks.
Demonstrated track record of influential projects and publications in relevant fields and top-tier conferences and journals (such as NeurIPS, ICML, AAAI, CHI, UIST). Demonstrated interdisciplinary experience in applied machine learning, natural language processing, and human computer interaction including experience doing offline and online evaluations, and conducting user studies and user-centered research. Exceptional coding experience and hands-on experience working with large foundation models and related frameworks and toolkits. Familiarity with LLMs such as the OpenAI Generative Pre-Trained Transformers (GPT) models, LLAMA etc., model finetuning techniques (LORA, QLORA), prompting techniques (Chain of Thought, ReACT etc.) and model evaluation is beneficial.
A passion for innovation and creativity, evidenced by the ability to generate novel ideas, approaches, and solutions. A team player mindset, characterized by effective communication, collaboration, and feedback skills.

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 Perform cutting-edge research to solve real-world problems. Collaborate closely with other researchers, engineers, and product group partners on high-impact projects that deliver real-world impact to people and society. Embody our culture and values.

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.

London

Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

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

Challenges you will own Conducting cutting-edge research in NeRFs, Gaussian splatting, and related technologies, with a focus on solving real-world challenges in 3D rendering Developing and implementing algorithms for efficient, high-quality 3D scene reconstruction and rendering, particularly for dynamic and outdoor environments Collaborating with cross-functional teams to integrate research findings into scalable, production-level solutions Staying abreast of the latest developments in the field, evaluating and incorporating state-of-the-art techniques into our workflows Potentially finding opportunities to publish research findings in top-tier journals and conferences, contributing to the scientific community and establishing Wayve as a leader in the field What you will bring to Wayve Essential Proven track record of research in NeRFs, Gaussian splatting, or closely related areas, demonstrated through publications or deployed applications Strong programming skills in Python with experience in deep learning frameworks such as PyTorch Solid foundation in mathematics and physics underlying 3D graphics and rendering techniques Excellent problem-solving skills and the ability to work independently as well as in a team environment Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment

Desirable Experience with dynamic scene reconstruction and rendering, particularly in outdoor environments Familiarity with parallel computing, GPU programming, and optimization techniques PhD or MSc in Computer Science, Computer Engineering, or a related field, with a focus on computer graphics, computer vision, or machine learning What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact Competitive compensation and benefits A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day