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.

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".

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.

Redmond, Washington, United States

Overview Microsoft Research (MSR) AI Frontiers lab is seeking applications for the position of Senior Research Engineer – Generative AI to join their team in Redmond, WA and New York City, NY.

The mission of the AI Frontiers lab is to expand the pareto frontier of 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), foundation models for actions (e.g., in gaming, robotics, and Office productivity tools) and Multi-Agent AI (e.g. AutoGen).

We are seeking Senior Research Engineers to join our team and contribute to the advancement of Generative AI and Large Language Models (LLMs) technologies. As a Research Engineer, you will play a crucial role in 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 language models, action models 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 models to meet application-specific requirements Orchestration and multi-agent systems: automated orchestration between multiple agents incorporating human feedback and oversight

Microsoft Research (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.

Embody our Culture and Values

Responsibilities As a Senior Research Engineer in AI Frontiers, you will design, develop, execute, and implement technology research projects 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.

Seattle, WA; Costa Mesa, CA; Boston, MA

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

THE ROLE We build Lattice, the foundation for everything we do as a defense technology company. Our engineers are talented and hard-working, motivated to see their work rapidly deployed on the front lines. Our team is not just building an experiment in waiting, we deploy what we build on the Southern border, Iraq, Ukraine and more.

We have open roles across Platform Engineering, ranging from core infrastructure to distributed systems, web development, networking and more. We hire self-motivated people, those who hold a higher bar for themselves than anyone else could hold for them. If you love building infrastructure, platform services, or just working in high performing engineering cultures we invite you to apply!

YOU SHOULD APPLY IF YOU: -At least 3+ years working with a variety of programming languages such as Rust, Go, C++, Java, Python, JavaScript/TypeScript, etc. -Have experience working with customers to deliver novel software capabilities -Want to work on building and integrating model/software/hardware-in-the-loop components by leveraging first and third party technologies (related to simulation, data management, compute infrastructure, networking, and more). -Love building platform and infrastructure tooling that enables other software engineers to scale their output -Enjoy collaborating with team members and partners in the autonomy domain, and building technologies and processes which enable users to safely and rapidly develop and deploy autonomous systems at scale. -Are a U.S. Person because of required access to U.S. export controlled information

Note: The above bullet points describe the ideal candidate. None of us matched all of these at once when we first joined Anduril. We encourage you to apply even if you believe you meet only part of our wish list.

NICE TO HAVE -You've built or invented something: an app, a website, game, startup -Previous experience working in an engineering setting: a startup (or startup-like environment), engineering school, etc. If you've succeeded in a low structure, high autonomy environment you'll succeed here! -Professional software development lifecycle experience using tools such as version control, CICD systems, etc. -A deep, demonstrated understanding of how computers and networks work, from a single desktop to a multi-cluster cloud node -Experience building scalable backend software systems with various data storage and processing requirements -Experience with industry standard cloud platforms (AWS, Azure), CI/CD tools, and software infrastructure fundamentals (networking, security, distributed systems) -Ability to quickly understand and navigate complex systems and established code bases -Experience implementing robot or autonomous vehicle testing frameworks in a software-in-the-loop or hardware-in-the-loop (HITL) environment -Experience with modern build and deployment tooling (e.g. NixOS, Terraform) -Experience designing complex software systems, and iterating upon designs via a technical design review process -Familiarity with industry standard monitoring, logging, and data management tools and best practices -A bias towards rapid delivery and iteration

Redmond, Washington, United States

Overview The Azure AI Platform (AIP) provides organizations across the world with the tooling and infrastructure needed to build and host AI workloads. The AI Platform organization is scaling rapidly, and we are establishing a world-class data analytics platform to support data-driven decision making through the organization.

We are looking to hire a Senior Data Scientist to join the newly formed AI Platform Analytics team. This individual will be responsible for collaborating with teams across AI Platform to establish trustworthy data sets and provide actionable insights and analysis.

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

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

Apply your knowledge in quantitative analysis, data mining, and the presentation of data to inform decision-making. Build data manipulation, processing, and data visualization tools and share these tools and your knowledge across the team, Cloud and AI, and Microsoft. Handle large amounts of data using various tools, including your own. Ensure high-quality and reliable data. Drive end-to-end projects by utilizing, applying and analyzing data to associated business problems. Engage with Upper Level Management by making key business decisions. Mentor other team members. Contribute to data-driven culture by collaborating with product and engineering teams across Azure to establish and share best practices 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 Sr. Fullstack Engineer, you will work on our platform engineering team playing a crucial role in enabling our research engineers to fine-tune our foundation models and streamline the machine learning process for our autonomous technology. You will work on developing products that empower our internal teams to maximize efficiency and innovation in our product. Specifically, you will:

• Build mission-critical tools for improving observability and scaling the entire machine-learning process.
• Use modern technologies to serve huge amounts of data, visualize key metrics, manage our data inventory, trigger backend data processing pipelines, and more.
• Work closely with people across the company to create a seamless UI experience.

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).

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

Redmond, Washington, United States

Overview Within AI Platform, the Cognitive Services team empowers developers and data scientists around the world and of all skill levels to easily add AI capabilities to their apps. #aiplatform

We are looking for a Research Scientist with a background in Computer Vision, Natural Language Processing and/or Artificial Intelligence, including topics like layout analysis, chart understanding, multi-page multi-document question answering, novel ways of leveraging large language models for document understanding and solving problems inherent to large language models (grounding, retrieval-based generation, etc.). Familiarity with modern large language models is a plus, but not required.

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.

Responsibilities Your responsibilities will include:

Conduct pioneering research to propel the state-of-the-art in various tasks in document understanding. Work closely with fellow Research Scientists and Product Engineering teams to translate research outcomes into practical solutions. Provide expertise and support to the engineering team on various challenges, fostering collaboration between research and practical application. Take charge of the research agenda from problem definition to algorithm and model development.

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 Seattle, WA Palo Alto, CA

Description Amazon’s product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on an AI-first initiative to continue to improve the way we do search through the use of large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced multi-modal deep-learning models on very large scale datasets, specifically through the use of advanced systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge Computer Vision and Deep Learning technologies and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: * How can multi-modal inputs in deep-learning models help us deliver delightful shopping experiences to millions of Amazon customers? * Can combining multi-modal data and very large scale deep-learning models help us provide a step-function improvement to the overall model understanding and reasoning capabilities? We are looking for exceptional scientists who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.

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

Location Multiple Locations

Description

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet). We recently demonstrated the feasibility of running a foundation model (Stable Diffusion) with >1 billion parameters on an Android phone under one second after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

• Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

• Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

• Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

• Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

• Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

• Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

• Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).

Location Seattle, WA New York, NY

Description We are looking for an Applied Scientist to join our Seattle team. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. Our team solves a broad range of problems ranging from natural knowledge understanding of third-party shoppable content, product and content recommendation to social media influencers and their audiences, determining optimal compensation for creators, and mitigating fraud. We generate deep semantic understanding of the photos, and videos in shoppable content created by our creators for efficient processing and appropriate placements for the best customer experience. For example, you may lead the development of reinforcement learning models such as MAB to rank content/product to be shown to influencers. To achieve this, a deep understanding of the quality and relevance of content must be established through ML models that provide those contexts for ranking.

In order to be successful in our team, you need a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning. Our team utilizes a variety of AWS tools such as SageMaker, S3, and EC2 with a variety of skillset in shallow and deep learning ML models, particularly in NLP and CV. You will bring knowledge in many of these domains along with your own specialties.